Systems and methods for autonomous vehicle communication

ABSTRACT

The subject matter described herein presents various technical solutions for the technical problems facing autonomous vehicles (e.g., fully autonomous and semi-autonomous vehicles). To address technical problems facing wireless communication cost and latency, a heterogeneous roadside infrastructure can be used to improve the ability for a vehicle to communicate with a data source. To address technical problems facing interruption of vehicle services due to an abrupt loss of connection, a quality of service system provides the ability to determine and share quality of service information, such as location-based information, maps, interference data, and other quality of service information. To address technical problems facing high volume data upload and download between autonomous vehicles and cloud-based data services, optical wireless communication (OWC) provides increased data throughput and reduced complexity, and may be beneficial for short-range high-mobility wireless communications.

TECHNICAL FIELD

Some aspects of the present disclosure relate to vehicle navigation.More specifically, some aspects relate to vehicle data communicationduring vehicle navigation.

BACKGROUND

Modern vehicles may upload or download significant amounts of data. Forexample, autonomous vehicles may upload data continually to the cloud(e.g., a data center, a cloud computing environment, and othercloud-based data environments), data that may be used for tuningautonomous driving algorithms based on individual data or based on testvehicle fleets. Vehicles may also continually download data, such asreal-time surrounding car data, map downloads, media downloads, or otherdata. Although some wireless communication (e.g., 5G) channels mayprovide high data bandwidth, these communication channels often requireexpensive vehicle data plans. Other wireless communication protocols,such as Wi-Fi and WiGig technologies, provide data communication butwith significant bandwidth (e.g., bits per second throughput)constraints for large amounts of data. The performance of each of thesecommunication protocols may be reduced further, such as due to non-lineof sight communications and outdoor environment challenges. What isneeded is an improved solution for transmission of vehicular data.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a diagram depicting an exemplary heterogeneous infrastructure,in accordance with some aspects.

FIG. 2 is a diagram depicting a heterogeneous infrastructure contentdistribution system, in accordance with some aspects.

FIG. 3 is a diagram depicting a first vehicle service access flow, inaccordance with some aspects.

FIG. 4 is a diagram depicting a second vehicle service access flow, inaccordance with some aspects.

FIG. 5 is a diagram depicting a third vehicle service access flow, inaccordance with some aspects.

FIG. 6 is a diagram depicting a vehicle communication quality of service(QoS) system, in accordance with some aspects.

FIG. 7 is a diagram depicting a dynamic network reconfiguration system,in accordance with some aspects.

FIG. 8 is a diagram depicting an optical wireless communication (OWC)deployment, in accordance with some aspects.

FIG. 9 is a diagram depicting a collimated OWC configuration, inaccordance with some aspects.

FIG. 10 is a diagram depicting an OWC customized optical front-enddesign, in accordance with some aspects.

FIGS. 11A and 11B are diagrams of customized optical front-endperformance, in accordance with some aspects.

FIG. 12 is a block diagram of a radio architecture in accordance withsome aspects.

FIG. 13 illustrates a front-end module circuitry for use in the radioarchitecture of FIG. 12 in accordance with some aspects.

FIG. 14 illustrates a radio IC circuitry for use in the radioarchitecture of FIG. 12 in accordance with some aspects.

FIG. 15 illustrates a baseband processing circuitry for use in the radioarchitecture of FIG. 12 in accordance with some aspects.

FIG. 16 illustrates a block diagram of an example machine for performingmethods according to some aspects.

FIG. 17 illustrates an example of a user equipment (UE) device accordingto some aspects.

FIG. 18 illustrates an example UE and a base station (BS) such as anEvolved Node-B (eNB) or Next Generation Node-B (gNB) according to someaspects.

To identify the discussion of any particular element or act, the mostsignificant digit or digits in a reference number refer to the figurenumber in which that element is first introduced. Further, like numbersindicate like components.

DETAILED DESCRIPTION

The subject matter described herein presents various technical solutionsfor the technical problems facing autonomous vehicles (e.g., fullyautonomous and semi-autonomous vehicles). To address technical problemsfacing wireless communication cost and latency, a heterogeneous roadsideinfrastructure can be used to improve the ability for a vehicle tocommunicate with a data source. To address technical problems facinginterruption of vehicle services due to an abrupt loss of connection, aquality of service system provides the ability to determine and sharequality of service information, such as location-based information,maps, interference data, and other quality of service information. Toaddress technical problems facing high volume data upload and downloadbetween autonomous vehicles and cloud-based data services, opticalwireless communication (OWC) provides increased data throughput andreduced complexity, and may be beneficial for short-range high-mobilitywireless communications.

The description that follows includes systems, methods, techniques,instruction sequences, and computing machine program products thatembody illustrative aspects of the disclosure. In the followingdescription, for the purposes of explanation, numerous specific detailsare set forth in order to provide an understanding of various aspects ofthe inventive subject matter. It will be evident, however, to thoseskilled in the art, that aspects of the inventive subject matter may bepracticed without these specific details. In general, well-knowninstruction instances, protocols, structures, and techniques are notnecessarily shown in detail.

FIG. 1 is a diagram depicting an exemplary heterogeneous infrastructure100, in accordance with some aspects. To support the increasing numberof autonomous vehicles, there is a need to provide improved services tothe vehicles. These services may rely on communication between thevehicle and a data source, such as the cloud. These services may includereal-time services, such as smart parking, providing over-the-air (OTA)updates for vehicle software, firmware, and security patches, providingtraffic and weather alerts in real-time that are specific to the vehiclelocation, providing entertainment and office services for passengers,downloading and updating of high definition (HD) maps (e.g., high levelof three-dimensional navigation detail) during a drive, and otherservices. The continuous dependency of these services on the cloud(including, e.g., wide-area networks (WANs), the Internet, and othercloud-based data connections) increases network cost for carriers.Further, the current wireless carriers may not have sufficient bandwidthfor real-time services, where even 5G access often includes severalsequential communication paths (e.g., communication hops) between thevehicle and the cloud, where each communication path adds to latency.

To provide improved vehicle services, the heterogeneous infrastructure100 improves the ability for a vehicle to communicate with a datasource. In particular, heterogeneous infrastructure 100 provides aheterogeneous infrastructure along a road. In some aspects, thisheterogeneous infrastructure 100 allows vehicular services to be servedby multiple infrastructure owners seamlessly as a vehicle passes bymultiple access nodes implemented in roadside devices. Theinfrastructure may include these access nodes implemented in roadsidedevices, where the access nodes may include edge nodes 110, streetlights 112, roadside units (RSUs) 114, traffic lights 116, or other fogor edge computing nodes. A vehicle 120 may communicate through edgenodes 110 or other roadside devices, through a multi-access edgecomputing (MEC) device 108, and through a content delivery network (CDN)device 104 to data stored in cloud servers 102. In operation, eachservice provider may advertise existing services to vehicles through theclosest point to each vehicle. The service provider may include a homecarrier for the vehicle, a foreign carrier, or a foreign non-carrierservice provider. In an aspect, the service provider includes anover-the-top (OTT) player. Using the heterogeneous infrastructure 100,vehicles may subscribe on-demand to each needed service, and may haveseamless access to services from the heterogeneous infrastructure 100directly, independent of the service provider. In an aspect, a homecarrier for the vehicle subscription may remain the point of contact forauthentication of the vehicle for service access from any serviceprovider or carrier.

The heterogeneous infrastructure 100 may improve the operation ofautonomous vehicle services by supporting services that are regional anddo not require continuous communication with the backend cloud. Theheterogeneous infrastructure 100 provides an infrastructure that isheterogeneous in that it provides the ability for vehicles to discoverand access available services, and the ability to provide seamlessservices access to vehicles across the heterogeneous infrastructure 100and heterogeneous services providers. For example, a vehicle 120 maycommunicate with an RSU 114 back to cloud servers 102, which may provideinformation about services available at that RSU 114 and other RSUs inthe vicinity or in the direction of travel. This sharing of informationacross access nodes improves availability of information regardingavailable services provided by carriers and service providers, whichimproves the ability of a home carrier or service providers to provideto their subscribers' vehicles the list of available services from anycarrier or service provider at any time in any region. This sharing ofinformation across access nodes also improves real-time services andservices continuity, which improves the performance of communication toand from connected and autonomous vehicles.

From the perspective of the vehicle operator, this heterogeneousinfrastructure 100 provides transparent service access for autonomousvehicles with horizontal and vertical roaming. For example, the providedhorizontal roaming allows continuous services access with servicesroaming across the infrastructure of the same provider, and the providedvertical roaming allows continuous services access with services roamingacross the infrastructure of different service providers. Thisheterogeneous infrastructure 100 provides a distributed infrastructureas multi-tenant to service providers, which is used to provide seamlessservice access to an autonomous vehicle based on the servicesadvertisement data set and for any service provider.

In addition to improving the provision of real-time services forvehicles, the heterogeneous infrastructure 100 may provide the abilityof a service or hardware provider (e.g., MEC provider, fog nodeprovider) to improve vehicle safety by improving autonomous vehiclemapping through improved gathering of vehicular data. The use ofroadside devices also improves the ability of a city or other area toimprove provisioning of other services, such as for smart city andadditional road services.

FIG. 2 is a diagram depicting a heterogeneous infrastructure contentdistribution system 200, in accordance with some aspects. The contentdistribution system 200 includes a service content source, such as acloud 202. The cloud 202 communicates with one or more service contenttrackers and storage devices, such as one or more CDNs 204 and one ormore service trackers 205. The service trackers 205 for differenceservices share information through a services tracker orchestrator 206,such as information regarding the type of service and the location ofthe service in the CDN 204. In some aspects, a point-to-point (P2P)protocol (e.g., peer-to-peer streaming protocol (PPSP)) may be used forthis information sharing.

The services tracker orchestrator 206 in turn communicates with one ormore fog node communication devices, such as eNodeB 211. Each eNodeB 211may have an associated mobile edge computing (MEC) device 210. Each MECdevice acts as an extension of each CDN 204, such as by providingnetwork-based caching of content for services from diverse CDNproviders. A service publication list 213 is distributed to vehicles,such as directly by each MEC 210 or indirectly through one or more RSUs214. The MEC 210 or RSUs 214 may be positioned along the road, and mayquery the services tracker orchestrator 206 about content locations forservices across the various CDNs 204. This query may take place througha P2P protocol, such as PPSP. In an aspect, each of the RSUs 214 may getinformation in real-time from one or more of the MECs 210 or the RSUs214 on available services through a subscription protocol, such asmessage queuing telemetry transport (MQTT) protocol. Vehicles positionedor traveling along the road get information on available services andtheir location across the heterogonous infrastructure from RSUs 214,MECs 210, or through eNodeB 211 fog nodes. Using this information, thevehicles may select the services needed by the vehicle based on servicesto which the vehicle has access. The connectivity from RSUs 214 tovehicles can be through vehicle-to-everything (V2X) in LTE or 5Gcommunication infrastructures, or may use other wireless connectivity.The connectivity from RSUs 214 to the eNodeB 211 fog nodes and to theMECs 210 may include Millimeter Wave communication (mmWavecommunication). The connectivity from one or more of the MECs 210 tovarious CDNs 204 may include communication through wired optical orGigabit (Gbit) Ethernet communication links.

FIG. 3 is a diagram depicting a first vehicle service access flow 300,in accordance with some aspects. The first vehicle service access flow300 shows an example communication flow for vehicles service access fromcloud 302 (e.g., a home carrier cloud). The home carrier cloud 302associated with the vehicle may include the service provider for one ormore specific services that the vehicle needs on the road, such as mapsdistribution, providing over-the-air (OTA) updates, and other services.

In this aspect, the vehicle 320 uses an on-demand subscription toservices, such as services selected based on need per location or roadsegment. In operation, the cloud 203 provides a services content push toone or more CDNs 304, which in turn provide a services content push toone or more eNodeB fog nodes 311 or MECs 310. A services advertisementis provided to one or more RSUs 314 and to the vehicle 320. If there areno RSUs 314 on a road segment, the services advertisement may take placedirectly from the MEC 310. Vehicles 320 may provide a servicessubscription back to the MECs 310 to subscribe to services on-demand,such as using a pub-sub model such as MQTT. Finally, the MECs 310 mayprovide services access to the vehicle 320. Communication may take placethrough the carrier network infrastructure, which may includeauthentication and authorization for services access performed by thehome carrier 302 based on the vehicle's subscription to the service.

FIG. 4 is a diagram depicting a second vehicle service access flow 400,in accordance with some aspects. The second vehicle service access flow400 shows an example flow of vehicles access for services from anyservice provider or foreign carrier. In this aspect, a foreign carrierfor the vehicle may be the service provider for one or more servicesthat the vehicle needs on the road, or a service provider with which thevehicle has no subscription may cover the road segment with one or moreservices that the vehicle needs. The second vehicle service access flow400 provides access to those vehicle services.

In this aspect, the vehicle 420 uses an on-demand subscription toservices, such as services selected based on need per location or roadsegment. In operation, the RSUs 414 have information on availableservices, and the RSUs 414 provide a services advertisement to thevehicle 420. If there are no RSUs 414 on a road segment, the servicesadvertisement can take place directly from one or more MECs 410. Incontrast with the first vehicle service access flow 300, second vehicleservice access flow 400 may include one or more edge nodes 410. Eachedge node 410 may provide a services advertisement to the vehicle 420,and the vehicle may provide a services subscription back to the edgenode 410. To provide authentication and authorization for vehicle accessto particular services, the vehicle's home subscriber may be used as thetrusted party, such as using the authentication and authorization toservices access discussed below with respect to FIG. 5.

FIG. 5 is a diagram depicting a third vehicle service access flow 500,in accordance with some aspects. The third vehicle service access flow500 shows an aspect of handling authentication and authorization toservices access. In operation, a vehicle 520 may identify itself on itshome carrier subscription during a service request, such as using aninternational mobile subscriber identity (IMSI). The home carrier 502may be contacted by the service provider, such as by an RSU 514 or theby an edge node 510, to verify the authentication of the vehicle 520.The home carrier 502 may confirm authentication of the vehicle 520 andseparately send to the vehicle 520 a one-time decryption key (OTDK)(e.g., one-time numeric password) for the used service, and may send aone-time encryption key (OTEK) to the service provider serving node,such as to the edge node 510 or to the RSU 514. The service providerserving node may encrypt the service messages or packets being sent tothe vehicle using the OTEK, and the vehicle 520 receiving servicesmessages or packets may decrypt them using the OTDK. This allows trustedauthentication of the vehicle 520 through its home subscriber and freshkeys for services access on roads.

FIG. 6 is a diagram depicting a vehicle communication quality of service(QoS) system 600, in accordance with some aspects. The QoS system 600provides an improved ability to determine and share the communicationQoS, which improves the ability of an autonomous vehicle to handleinterruptions in network connectivity. For example, a vehicle 606 mayexperience an interruption of vehicle services due to an abrupt loss ofconnection, which causes a significant degradation to the quality ofexperience (QoE) of the users. This degradation may include reducing orpreventing access to real-time services for connected and autonomousvehicles, such as preventing real-time updates of maps. Additionally,many real-time autonomous vehicle applications operate based on anestimation of available throughput and latency, together with theservice bandwidth consumption needs and latency needs, to providevehicle service delivery requirements.

The QoS system 600 provides the ability to determine and share thecommunication QoS with moving autonomous vehicles. In vehicularenvironments where the cars are moving, particularly where vehicles aremoving with a very high speed compared to mobile users, the QoS system600 provides the ability to determine and share the communication QoSeven when the vehicle connectivity to the network may roam frequentlybetween base stations or access points. In an aspect, the QoS system 600may provide the ability of a vehicle to have advance knowledge ofconnectivity options, which allows adjustment of applications tominimize or avoid the service interruption. For example, when a vehicleis about to enter a tunnel or otherwise expects limited bandwidth, thecommunication QoS enables the vehicle to prioritize mapping or safetytraffic communication, and to notify the user. The predictive QoSestimation provided by QoS system 600 also improves the ability of avehicle to meet data connectivity requirements put forward by carmanufacturers for various consumer and other vehicle-to-everything (V2X)services. These requirements may include coverage information bydifferent communication technologies, throughput and latencyrequirements per service type, and other requirements.

To improve the determination and sharing of communication QoS, variouspredictive QoS adjustments may be used. In an aspect, a predictive QoSadjustment includes crowd-sourcing QoS information. In thecrowd-sourcing aspect, multiple vehicles may collect QoS information asthey move through an area and provide the QoS information back through anetwork to an application server. The collected QoS information mayinclude information about coverage, average latency, availablethroughput from different networks or interfaces, and other QoSinformation. The QoS information may be collected explicitly by one ormore dedicated sensors, or may be collected implicitly by analysis ofother available QoS information. The reporting of QoS information fromvehicles back to an application server may use high-overhead real-timereporting for information that affects real-time services, such asinformation for high definition (HD) maps download, traffic information,roadside alerts, and other real-time service information. The reportingof QoS information from vehicles back to an application server may uselow-overhead offline reporting at the end of the day, such as forconnectivity loss at a particular area all the time, packets drops inknown areas, for issues that appear permanent, or for issues that do nothave real-time significance. The reporting may be distributed directlyfrom a vehicle to other nearby vehicles using V2V communication, such ascommunicating QoS information to following cars or to cars approachingthe location.

In an aspect, a single vehicle may be designated as a reporting vehicle,and other nearby vehicles associated with the reporting vehicle mayreceive direct QoS information from the reporting vehicle. The QoSinformation reported by the cars may be processed at a network edgedevice. The QoS information may include location-based information, andthe location-based information may be used to generate a network QoE mapfor each region. The QoS map may indicate a level of quality for variouslocations, areas of interference, or other QoS information. In variousaspects, the region size may be identified as a predetermined area, suchas an area based on a predetermined number of square kilometers orsquare miles. The generated network QoE map provides the prediction ofQoE for services per region, and may be communicated to vehiclesapproaching that location or application sources, enabling othervehicles to adjust bandwidth parameters in advance to minimize oreliminate any interruption in service, such as by pre-buffering to cachethe data. The generated network QoE map may be refreshed continually bynew crowdsourcing.

As shown in FIG. 6, a QoS system 600 may provide a predictive QoSadjustment based on machine learning. The QoS system 600 includes anapplication server 602 and a machine learning (ML) device 604. Themachine learning device 604 may receive information from one or morevehicles 606, which may be collected and provided using crowdsourcing asdescribed above. The information may include information about theperformance of one or more autonomous navigation applications, vehiclemeasurements, QoE experienced at the vehicle 606, information about theusers, information about the vehicles, information about vehiclelocations, or other QoS information. The information may be correlatedas input for training of a QoS machine learning model at the machinelearning device 604. The machine learning device 604 may provide networkparameters to the application server 602 and receive applicationinformation from the application server 602. The machine learning device604 may receive application information from a vehicle 606 and provideQoS information back to the vehicle 606, such as providing a wirelesscommunication radio configuration instructing the radio to cacheinformation in anticipation of an upcoming service outage. In anexample, an application server 602 may work with machine learning device604 to learn over time that a user during morning commute goes through alow throughput area, and may cause caching of data at an edge networkdevice or pre-buffering at the vehicle device to reduce the effect oftraveling through the low throughput area.

In an aspect, the machine learning device 604 may train a QoS machinelearning model to identify an output combination of QoS networkparameters based on a particular pattern of received QoS information. Inanother aspect, the machine learning device 604 may train a QoS machinelearning model to identify an output wireless communication radioconfiguration based on an input pattern of received QoS information,based on application information received from the application server602, based on application information received from the vehicle 606, orbased on a real-time link quality experienced by a vehicle modem. In anaspect, the network parameters, application information, radioconfiguration, and other information may be used to generate apredictive QoS map, and that QoS map may be provided to other vehiclesto improve data-based vehicle service performance.

While FIG. 6 shows the machine learning device 604 separate from theapplication server 602 and the vehicles 606 and 608, the machinelearning may be executed on the application server 602 or on one or moreof the vehicles 606 and 608. For example, vehicle 606 may include themachine learning device 604 communicatively coupled to the vehicleapplications, and vehicle 608 may train its internal QoS machinelearning model based on frequent trips, frequently used vehicleservices, available and demanded resources, and other information.Information provided by a vehicle's internal QoS machine learning modelmay be provided back to an application server 602, which may use theinformation to generate a predictive QoS map. For example, the QoS mapmay be generated at the application server 602 and provided vehicle 606,which may use the QoS map to identify an area of decreased bandwidth andallocate additional slices of network bandwidth to vehicle 606 toincrease the effective bandwidth. This generate of predictive QoSinformation based on crowdsourcing or based on machine learning may beused to improve network reconfiguration, such as described below withrespect to FIG. 7.

FIG. 7 is a diagram depicting a dynamic network reconfiguration system700, in accordance with some aspects. System 700 enables dynamiclearning of connected and autonomous vehicles upstream and downstreamtraffic needs, which may be used to provide dynamic networkreconfiguration. System 700 includes one or more vehicle serviceapplications 702 that communicate with a vehicle modem 704. The vehiclemodem 704 receives configuration information from a vehicle serviceinspection knob (e.g., device) 706, such as service type, frequency,location dependence, performance requirements, or other inspectioninput. The vehicle modem 704 also receives configuration informationfrom a machine learning knob 708, which may be used to modify machinelearning parameters such as model training iteration count, modeltraining batch size, and other machine learning parameters. The vehiclemodem 704 uses information from the vehicle service inspection knob 706and the machine learning knob 708 to provide a channel adaptation knob710. The vehicle modem 704 may provide network coverage throughputthrough a roadside unit (RSU) 712 and through an eNodeB 714 to a mobileedge computing (MEC) server 716. The vehicle modem 704 may also providenetwork coverage throughput directly through the eNodeB 714 to the MECserver 716. The MEC server may communicate the network coveragethroughput to one or more network and service inspection knobs 718.

The MEC server 716 may be used to receive and store knowledge of networkcapacity and network loading, which may be used to help data carriers toconfigure real-time parameters to meet network QoS requirements. The MECserver 716 and network and service inspection knobs 718 may use machinelearning to receive and process dynamic information available about thevehicle service needs, consumption rate of services per road segment andtime of the day, density of services consumers on roads for vehicles androadside units, and dynamic information from vehicles. The MEC server716 and network and service inspection knobs 718 may generate dynamicinformation describing the vehicle service needs using deep packetinspection or intelligent traffic classification techniques applied todata provided from the vehicle modem 704. For example, the MEC server716 and network and service inspection knobs 718 may examine inreal-time the traffic types and vehicle service needs, and may adaptnetwork bandwidth slicing (e.g., allocation) for each vehicle servicetype in real-time. Dynamic information on the service needs may also beavailable via an interface to the application or via the vehicles, suchas using techniques for creation of predictive QoS map based oncrowdsourcing and machine learning described above with respect to FIG.6. The predictive QoS map generation and the dynamic networkreconfiguration may be used separately, though using both together wouldimprove or maximize the improvements to performance of data-basedvehicle services.

FIG. 8 is a diagram depicting an OWC deployment 800, in accordance withsome aspects. The OWC deployment 800 provides technical solutions forthe technical problems facing high volume data upload and downloadbetween autonomous vehicles and cloud-based data services. In someaspects, optical wireless communication (OWC) provides increased datathroughput and reduced complexity, such as may be beneficial forshort-range high-mobility wireless communications. These OWC solutionsprovide wireless access without requiring expensive wireless datapackages and reduces or eliminates interference with RF technologiessuch as Wi-Fi and WiGig. Table 1 summarizes how OWC outperforms WiGig:

TABLE 1 OWC Performance Vs. Wi-Fi OWC (Infrared) WiGig Capacity Per 10,25, 50 Gbit/s <7 Gbit/s Channel Up to 100 Gbit/s in development CarrierFrequency Center: 850 nm, 1310 nm, 1550 nm. Center: 60 GHz and AverageBW Ex: 1460-1625 (S + C + L) BW: 7 GHz Bandwidth width 20.9 THz SingleOWC alignment for achieving Big data paint duplex/multi-channel superhigh BW, point i.e., 1.1 Tbit/s (45λ * 25 Gbit/s) Interference Not withRF; Multi-wavelength Environment, beams interference are manageableexisting RF signals/ equipment

In various aspects, these OWC solutions can be leveraged when thevehicle is proximate to roadside units equipped with OWC in city roadsor highways. These solutions may be deployed in the transportationinfrastructure (e.g., traffic lights, light posts, vehicle chargingstations) to communicate with vehicles. Depending on the infrastructureimplementation, these OWC solutions may include a fixed point-to-pointOWC configuration (e.g., for charging station infrastructure) or a fixedpoint to moving point OWC configuration (e.g., for traffic light orlight posts infrastructures).

The OWC configuration 800 includes an example OWC solution for a fixedpoint to moving point OWC configuration, such as may be useful in thecase of download of a high volume data from the cloud to a vehicle. Inan aspect, a roadside environment 802 includes multiple roadside unitsto provide continuous coverage while a vehicle is moving. In an example,the transmitters may be installed in roadside barriers, which mayprovide continuous coverage even at high speeds.

Roadside snapshot 804 shows an example of this OWC solution. Morespecifically, the roadside snapshot 804 shows a vehicle 810communicating with an OWC roadside installation 806 within roadsideenvironment 802. The OWC roadside installation 804 includes a lightsource 806 that emits light-based signals 808. The light-based signals808 may use one or more wavelengths, where the wavelengths may beselected based on wavelength transmission effectiveness (e.g.,minimization of signal-to-noise ratio (SNR) levels), selected to providemultiple simultaneous channels of communication, or selected based onother criteria. The light-based signals 808 may be received by an OWCvehicle installation 812 installed on the vehicle 810. Each of the OWCroadside installation 806 and the OWC vehicle installation 812 mayinclude a light source transmitter and a photo detector receiver, suchas to provide simultaneous uploading and downloading.

Each OWC transmitter may be used to generate a light shower (e.g., anarea of illumination). The light shower provides a substantially uniformlight intensity at a predetermined distance, such as using one or morefocusing lenses described below. The predetermined distance for theuniform light intensity may include a range approximating a distancebetween the height of the OWC roadside installation 806 and an expectedaverage height of the OWC vehicle installation 812. In an example, thepredetermined distance may provide substantially uniform light intensityfor a range between three meters and four meters, though otherpredetermined distances and ranges may be used. By designing these OWCtransmitters to provide this substantially uniform light intensity, thereceiver on the OWC vehicle installation 812 receives substantiallyconsistent power levels while within the light cone (e.g., within thebroadcast area of the OWC roadside installation 806). Thesesubstantially consistent power levels provide substantially consistentSNR and improve the ability of the system to provide high bandwidthoperation. In an aspect, this substantially uniform intensity lightshower is provided by a collimated fiber output from the transmitterpassing through an optical front-end customized for the respective OWCinstallation. Outputs of multiple transmitters with different wavelengthmay be combined in the fiber (e.g., via a wavelength combiner). Usingthese features, the transmitter may provide the ability to use the sameoptical front-end while providing Dense Wave Division Multiplexing(DWDM). This DWDM may include multiplexed optical signals, such asoptical signals multiplexed within the 1550 nm band to leverage thecapabilities and cost of Erbium-doped fiber amplifiers (EDFAs), whichare effective for wavelengths between approximately 1525-1565 nm (Cband), or 1570-1610 nm (L band). The use of DWDM OWC may furtherincrease bandwidth. In an example, the DWDM OWC may provide a bandwidthof 45×25 Gbps=1.1 Tbps or higher. In some aspects, the data may bemodulated using on-off keying with Manchester encoding.

In some aspects, the OWC receiver may include focusing optics and aphoto detector receiver. The focusing optics may be used to focus light,such as focusing light directly onto the photo detector or focusinglight onto an optical fiber that brings the signal to the photodetector. An OWC receiver may include one or more detectors, and thedetector with the highest strength may be selected based on whichcombination provides the best signal (e.g., highest power level, lowestSNR). An OWC receiver may further include multiple detectors arrangedrelative to each other in various configurations, such as convexdetectors 814 or concave detectors 816. These nonplanar configurationsmay be used to increase the overall field of view of each receiver unit.Each receiver or detector may be mechanically actuated, such as to tracka receiver location or an incoming beam direction to improve or maximizedata coupling (e.g., improve or maximize SNR). In an aspect, thetracking of receiver location or beam direction may be based on currentknowledge of receiver location and a priori knowledge of transmitterlocation (e.g., offline download of transmitter locations). Using theselocations, the OWC receiver or receiver optics may be adjusted to pointtoward the transmitter location. In an aspect, the data coupling may beimproved or maximized by mechanically manipulating one or all of thereceiver optics, detector, or fiber, such as to obtain the highestsignal. Signal processing techniques may be employed to create a closedloop feedback directly from a detector, which may be used to search andalign to the optimal receiving position automatically for the receiverand or individual detectors in the receiver. By using an analysis basedon an assumption of a strongly Rician channel (e.g., channel with strongline-of-sight component), the complexity of the decision feedbackequalizer may be reduced to eliminate post-cursor inter-symbolinterference. For aspects using DWDM, a fiber wavelength filter may beused to separate wavelengths and bring them to individual receivers ordetectors.

FIG. 9 is a diagram depicting a collimated OWC configuration 900, inaccordance with some aspects. Fixed point-to-point OWC may providerobust and high-bandwidth download and upload links, such as by reducingor eliminating the effects of contact contamination failures. As shownin the collimated OWC configuration 900, a first lens 904 may be used tocollimate a transmission light signal 902 into a collimated light signal906, which may be received by a second lens 908 and focus the receivedlight signal 910 onto a receiver. Each of the first lens 904 and thesecond lens 908 may include a substantially aberration-free collimationlens, which may provide substantially 100% coupling for an OWC fixedpoint-to-point link. Each of the first lens 904 and the second lens 908may be used to collimate or focus light, supporting bi-directionalcommunication. Bi-directional communication may be further improved byusing an optical circulator to separate transmitting and receivingsignal on each side. Additionally, this OWC configuration 900 provides asimplified upgrade path to a higher bandwidth solution (e.g., amulti-wavelength MUX), such as by replacing transceiver or receivercomponents and reusing the fixed point-to-point collimated alignment OWCconfiguration 900.

FIG. 10 is a diagram depicting an OWC customized optical front-enddesign 1000, in accordance with some aspects. A light signal input 1002may be fed to a customized OWC lens 1004. The light signal input 1002may include light with a collimated Gaussian intensity profile (e.g.,brighter center, illumination following a bell-shaped plot). Thecustomized OWC lens 1004 may refocus the light signal input 1002 througha conical light cone 1006 onto a substantially planar and substantiallyuniform intensity light distribution 1008. The customized OWC lens 1004generates this light distribution 1008 using the aspherical surfaceproperty of the lens, focusing the collimated beam at different focalpoints near the lens in order to redistribute the intensity in asubstantially planar area at a predetermined designed distance. Thiscustomized OWC lens 1004 may be designed for various areas anddistances, such as using lens modelling software to identify auniformity target and to optimize the lens aspherical coefficients.While FIG. 10 shows a substantially uniform light distribution 1008 thatis circular or elliptical, other planar shapes may be selected forvarious environments and applications. For example, the OWC lens 1004may be designed for various conical angles, such as to provide anelliptical shape that is longer in a vehicle travel direction andnarrower in a direction perpendicular to vehicle travel. These designselections may be used to further improve or maximize SNR and overallsystem power efficiency.

FIGS. 11A and 11B are diagrams of customized optical front-endperformance 1100, in accordance with some aspects. FIG. 11A shows anexample of substantially uniform intensity in a two-dimensional plot. Inparticular, the light intensity is maximized and substantially uniformwithin circle 1104, but substantially zero intensity in the outer area1102. FIG. 11B shows an example of substantially uniform intensity in aone-dimensional plot. In particular, the light intensity is maximizedand substantially uniform within the desired area 1106, butsubstantially zero intensity in the outer area 1108. In an example, thecenter of the two-dimensional plot in FIG. 11A may correspond to thecenter line of the one-dimensional plot shown in FIG. 11B. By usingmodeling in designing the OWC customized optical front-end, the opticalfront-end may provide a substantially uniform intensity for apredetermined distance, and may also provide a substantially uniformintensity for a range of distances. This ability to provide asubstantially uniform intensity for a range of distances furtherimproves or maximizes SNR and overall system power efficiency for thevariations in communication ranges specific to these proposedinfrastructure and vehicle communication applications.

These light intensity patterns and optical front-end design may be usedto detect the use of the OWC aspects described herein. For example, thespecific lens configurations described above may be detected throughsystem analysis (e.g., reverse engineering). Additionally, thewavelength of the OWC light signals would likely include light withinthe near-IR spectrum range, and this transmitter output pattern may bedetected using an IR card or beam scanner.

FIG. 12 is a block diagram of a radio architecture 1200 in accordancewith some aspects. Radio architecture 1200 may be used to provide radiocommunication, such as for the heterogeneous infrastructure 100, thevehicle QoS system 600, or other systems described herein. Radioarchitecture 1200 may include radio front-end module (FEM) circuitry1204, radio IC circuitry 1206 and baseband processing circuitry 1208.Radio architecture 1200 as shown includes both Wireless Local AreaNetwork (WLAN) functionality and Bluetooth (BT) functionality althoughaspects are not so limited. In this disclosure, “WLAN” and “Wi-Fi” areused interchangeably.

FEM circuitry 1204 may include a WLAN or Wi-Fi FEM circuitry 1204A and aBluetooth (BT) FEM circuitry 1204B. The WLAN FEM circuitry 1204A mayinclude a receive signal path comprising circuitry configured to operateon WLAN RF signals received from one or more antennas 1201, to amplifythe received signals and to provide the amplified versions of thereceived signals to the WLAN radio IC circuitry 1206A for furtherprocessing. The BT FEM circuitry 1204B may include a receive signal pathwhich may include circuitry configured to operate on BT RF signalsreceived from one or more antennas 1201, to amplify the received signalsand to provide the amplified versions of the received signals to the BTradio IC circuitry 1206B for further processing. FEM circuitry 1204A mayalso include a transmit signal path which may include circuitryconfigured to amplify WLAN signals provided by the radio IC circuitry1206A for wireless transmission over a wireless communication network byone or more of the antennas 1201. In addition, FEM circuitry 1204B mayalso include a transmit signal path which may include circuitryconfigured to amplify BT signals provided by the radio IC circuitry1206B for wireless transmission by the one or more antennas. In theaspect of FIG. 12, although FEM circuitry 1204A and FEM circuitry 1204Bare shown as being distinct from one another, aspects are not solimited, and include within their scope the use of additional FEMcircuitry (not shown) that includes a transmit path or a receive pathfor both WLAN and BT signals, or the use of one or more FEM circuitrieswhere at least some of the FEM circuitries share transmit or receivesignal paths for both WLAN and BT signals.

Radio IC circuitry 1206 as shown may include WLAN radio IC circuitry1206A and BT radio IC circuitry 1206B. The WLAN radio IC circuitry 1206Amay include a receive signal path which may include circuitry todown-convert WLAN RF signals received from the FEM circuitry 1204A andprovide baseband signals to WLAN baseband processing circuitry 1208A. BTradio IC circuitry 1206B may in turn include a receive signal path whichmay include circuitry to down-convert BT RF signals received from theFEM circuitry 1204B and provide baseband signals to BT basebandprocessing circuitry 1208B. WLAN radio IC circuitry 1206A may alsoinclude a transmit signal path which may include circuitry to up-convertWLAN baseband signals provided by the WLAN baseband processing circuitry1208A and provide WLAN RF output signals to the FEM circuitry 1204A forsubsequent wireless transmission by the one or more antennas 1201. BTradio IC circuitry 1206B may also include a transmit signal path whichmay include circuitry to up-convert BT baseband signals provided by theBT baseband processing circuitry 1208B and provide BT RF output signalsto the FEM circuitry 1204B for subsequent wireless transmission by theone or more antennas 1201. In the aspect of FIG. 12, although radio ICcircuitries 1206A and 1206B are shown as being distinct from oneanother, aspects are not so limited, and include within their scope theuse of a radio IC circuitry (not shown) that includes a transmit signalpath or a receive signal path for both WLAN and BT signals, or the useof one or more radio IC circuitries where at least some of the radio ICcircuitries share transmit or receive signal paths for both WLAN and BTsignals.

Baseband processing circuity 1208 may include a WLAN baseband processingcircuitry 1208A and a BT baseband processing circuitry 1208B. The WLANbaseband processing circuitry 1208A may include a memory, such as, forexample, a set of RAM arrays in a Fast Fourier Transform or Inverse FastFourier Transform block (not shown) of the WLAN baseband processingcircuitry 1208A. Each of the WLAN baseband circuitry 1208A and the BTbaseband circuitry 1208B may further include one or more processors andcontrol logic to process the signals received from the correspondingWLAN or BT receive signal path of the radio IC circuitry 1206, and toalso generate corresponding WLAN or BT baseband signals for the transmitsignal path of the radio IC circuitry 1206. Each of the basebandprocessing circuitries 1208A and 1208B may further include physicallayer (PHY) and medium access control layer (MAC) circuitry, and mayfurther interface with application processor 1210 for generation andprocessing of the baseband signals and for controlling operations of theradio IC circuitry 1206.

Referring still to FIG. 12, according to the shown aspect, WLAN-BTcoexistence circuitry 1213 may include logic providing an interfacebetween the WLAN baseband circuitry 1208A and the BT baseband circuitry1208B to enable use cases requiring WLAN and BT coexistence. Inaddition, a switch 1203 may be provided between the WLAN FEM circuitry1204A and the BT FEM circuitry 1204B to allow switching between the WLANand BT radios according to application needs. In addition, although theantennas 1201 are depicted as being respectively connected to the WLANFEM circuitry 1204A and the BT FEM circuitry 1204B, aspects includewithin their scope the sharing of one or more antennas as between theWLAN and BT FEMs, or the provision of more than one antenna connected toeach of FEM circuitry or FEM circuitry 1204B.

In some aspects, the front-end module circuitry 1204, the radio ICcircuitry 1206, and baseband processing circuitry 1208 may be providedon a single radio card, such as wireless radio card 1202. In some otheraspects, the one or more antennas 1201, the FEM circuitry 1204 and theradio IC circuitry 1206 may be provided on a single radio card. In someother aspects, the radio IC circuitry 1206 and the baseband processingcircuitry 1208 may be provided on a single chip or integrated circuit(IC), such as IC 1212.

In some aspects, the wireless radio card 1202 may include a WLAN radiocard and may be configured for Wi-Fi communications, although the scopeof the aspects is not limited in this respect. In some of these aspects,the radio architecture 1200 may be configured to receive and transmitorthogonal frequency division multiplexed (OFDM) or orthogonal frequencydivision multiple access (OFDMA) communication signals over amulticarrier communication channel. The OFDM or OFDMA signals maycomprise a plurality of orthogonal subcarriers.

In some of these multicarrier aspects, radio architecture 1200 may bepart of a Wi-Fi communication station (STA) such as a wireless accesspoint (AP), a base station or a mobile device including a Wi-Fi device.In some of these aspects, radio architecture 1200 may be configured totransmit and receive signals in accordance with specific communicationstandards or protocols, such as any of the Institute of Electrical andElectronics Engineers (IEEE) standards including, 802.11n-2009, IEEE802.11-2012, 802.11n-2009, 802.11ac, or 802.11ax standards or proposedspecifications for WLANs, although the scope of aspects is not limitedin this respect. Radio architecture 1200 may also be suitable totransmit or receive communications in accordance with other techniquesand standards.

In some aspects, the radio architecture 1200 may be configured forhigh-efficiency (HE) Wi-Fi (HEW) communications in accordance with theIEEE 802.11ax standard. In these aspects, the radio architecture 1200may be configured to communicate in accordance with an OFDMA technique,although the scope of the aspects is not limited in this respect.

In some other aspects, the radio architecture 1200 may be configured totransmit and receive signals transmitted using one or more othermodulation techniques such as spread spectrum modulation (e.g., directsequence code division multiple access (DS-CDMA) or frequency hoppingcode division multiple access (FH-CDMA)), time-division multiplexing(TDM) modulation, or frequency-division multiplexing (FDM) modulation,although the scope of the aspects is not limited in this respect.

In some aspects, as further shown in FIG. 12, the BT baseband circuitry1208B may be compliant with a Bluetooth (BT) connectivity standard suchas Bluetooth, Bluetooth 4.0 or Bluetooth 5.0, or any other iteration ofthe Bluetooth Standard. In aspects that include BT functionality asshown for example in FIG. 12, the radio architecture 1200 may beconfigured to establish a BT synchronous connection oriented (SCO) linkand or a BT low energy (BT LE) link. In some of the aspects that includea SCO functionality, the radio architecture 1200 may be configured toestablish an extended SCO (eSCO) link for BT communications, althoughthe scope of the aspects is not limited in this respect. In some ofthese aspects that include a BT functionality, the radio architecturemay be configured to engage in a BT Asynchronous Connection-Less (ACL)communications, although the scope of the aspects is not limited in thisrespect. In some aspects, as shown in FIG. 12, the functions of a BTradio card and WLAN radio card may be combined on a single wirelessradio card, such as single wireless radio card 1202, although aspectsare not so limited, and include within their scope discrete WLAN and BTradio cards

FIG. 13 illustrates FEM circuitry 1300 in accordance with some aspects.The FEM circuitry 1300 is one example of circuitry that may be suitablefor use as the WLAN or BT FEM circuitry 1204A or 1204B (FIG. 12),although other circuitry configurations may also be suitable.

In some aspects, the FEM circuitry 1300 may include a TX/RX switch 1302to switch between transmit mode and receive mode operation. The FEMcircuitry 1300 may include a receive signal path and a transmit signalpath. The receive signal path of the FEM circuitry 1300 may include alow-noise amplifier (LNA) 1306 to amplify received RF signals 1303 andprovide the amplified received RF signals 1307 as an output (e.g., tothe radio IC circuitry 1400 (FIG. 14)). The transmit signal path of theFEM circuitry 1300 may include a power amplifier (PA) to amplify inputRF signals 1309 (e.g., provided by the radio IC circuitry 1400), and oneor more filters 1312, such as band-pass filters (BPFs), low-pass filters(LPFs) or other types of filters, to generate RF signals 1315 forsubsequent transmission (e.g., by one or more of the antennas 1201 (FIG.12)).

In some dual-mode aspects for Wi-Fi communication, the FEM circuitry1300 may be configured to operate in either the 2.4 GHz frequencyspectrum or the 5 GHz frequency spectrum. In these aspects, the receivesignal path of the FEM circuitry 1300 may include a receive signal pathduplexer 1304 to separate the signals from each spectrum as well asprovide a separate LNA 1306 for each spectrum as shown. In theseaspects, the transmit signal path of the FEM circuitry 1300 may alsoinclude a power amplifier 1310 and a filter 1312, such as a BPF, a LPFor another type of filter for each frequency spectrum and a transmitsignal path duplexer 1314 to provide the signals of one of the differentspectrums onto a single transmit path for subsequent transmission by theone or more of the antennas 1201 (FIG. 12). In some aspects, BTcommunications may utilize the 2.4 GHZ signal paths and may utilize thesame FEM circuitry 1300 as the one used for WLAN communications.

FIG. 14 illustrates radio IC circuitry 1400 in accordance with someaspects. The radio IC circuitry 1400 is one example of circuitry thatmay be suitable for use as the WLAN or BT radio IC circuitry 1206A or1206B (FIG. 12), although other circuitry configurations may also besuitable.

In some aspects, the radio IC circuitry 1400 may include a receivesignal path and a transmit signal path. The receive signal path of theradio IC circuitry 1400 may include at least mixer circuitry 1402, suchas, for example, down-conversion mixer circuitry, amplifier circuitry1406 and filter circuitry 1408. The transmit signal path of the radio ICcircuitry 1400 may include at least filter circuitry 1412 and mixercircuitry 1414, such as, for example, up-conversion mixer circuitry.Radio IC circuitry 1400 may also include synthesizer circuitry 1404 forsynthesizing an output frequency 1405 for use by the mixer circuitry1402 and the mixer circuitry 1414. The mixer circuitry 1402 or 1414 mayeach, according to some aspects, be configured to provide directconversion functionality. The latter type of circuitry presents a muchsimpler architecture as compared with standard super-heterodyne mixercircuitries, and any flicker noise brought about by the same may bealleviated for example through the use of OFDM modulation. FIG. 14illustrates only a simplified version of a radio IC circuitry, and mayinclude, although not shown, aspects where each of the depictedcircuitries may include more than one component. For instance, mixercircuitry 1420 or 1414 may each include one or more mixers, and filtercircuitries 1408 or 1412 may each include one or more filters, such asone or more BPFs or LPFs according to application needs. For example,when mixer circuitries are of the direct-conversion type, they may eachinclude two or more mixers.

In some aspects, mixer circuitry 1402 may be configured to down-convertRF signals 1307 received from the FEM circuitry 1300 (FIG. 13) based onthe synthesized output frequency 1405 provided by synthesizer circuitry1404. The amplifier circuitry 1406 may be configured to amplify thedown-converted signals and the filter circuitry 1408 may include a LPFconfigured to remove unwanted signals from the down-converted signals togenerate output baseband signals 1407. Output baseband signals 1407 maybe provided to the baseband processing circuitry 1208 (FIG. 12) forfurther processing. In some aspects, the output baseband signals 1407may be zero-frequency baseband signals, although this is not arequirement. In some aspects, mixer circuitry 1402 may comprise passivemixers, although the scope of the aspects is not limited in thisrespect.

In some aspects, the mixer circuitry 1414 may be configured toup-convert input baseband signals 1411 based on the synthesizedfrequency 1405 provided by the synthesizer circuitry 1404 to generate RFoutput signals 1409 for the FEM circuitry 1300. The baseband signals1411 may be provided by the baseband processing circuitry 1208 and maybe filtered by filter circuitry 1412. The filter circuitry 1412 mayinclude a LPF or a BPF, although the scope of the aspects is not limitedin this respect.

In some aspects, the mixer circuitry 1402 and the mixer circuitry 1414may each include two or more mixers and may be arranged for quadraturedown-conversion or up-conversion respectively with the help ofsynthesizer circuitry 1404. In some aspects, the mixer circuitry 1402and the mixer circuitry 1414 may each include two or more mixers eachconfigured for image rejection (e.g., Hartley image rejection). In someaspects, the mixer circuitry 1402 and the mixer circuitry 1414 may bearranged for direct down-conversion or direct up-conversion,respectively. In some aspects, the mixer circuitry 1402 and the mixercircuitry 1414 may be configured for super-heterodyne operation,although this is not a requirement.

Mixer circuitry 1402 may comprise, according to one aspect: quadraturepassive mixers (e.g., for the in-phase (I) and quadrature phase (Q)paths). In such an aspect, RF input signal 1407 from FIG. 14 may bedown-converted to provide I and Q baseband output signals to be sent tothe baseband processor

Quadrature passive mixers may be driven by zero and ninety degreetime-varying LO switching signals provided by a quadrature circuitrywhich may be configured to receive a LO frequency (fLO) from a localoscillator or a synthesizer, such as LO output frequency 1405 ofsynthesizer circuitry 1404 (FIG. 14). In some aspects, the LO frequencymay be the carrier frequency, while in other aspects, the LO frequencymay be a fraction of the carrier frequency (e.g., one-half the carrierfrequency, one-third the carrier frequency). In some aspects, the zeroand ninety degree time-varying switching signals may be generated by thesynthesizer, although the scope of the aspects is not limited in thisrespect.

In some aspects, the LO signals may differ in duty cycle (the percentageof one period in which the LO signal is high) or offset (the differencebetween start points of the period). In some aspects, the LO signals mayhave a 25% duty cycle and a 50% offset. In some aspects, each branch ofthe mixer circuitry (e.g., the in-phase (I) and quadrature phase (Q)path) may operate at a 25% duty cycle, which may result in a significantreduction of power consumption.

The RF input signal 1407 (FIG. 14) may comprise a balanced signal,although the scope of the aspects is not limited in this respect. The Iand Q baseband output signals may be provided to low-nose amplifier,such as amplifier circuitry 1406 (FIG. 14) or to filter circuitry 1408(FIG. 14).

In some aspects, the output baseband signals 1407 and the input basebandsignals 1411 may be analog baseband signals, although the scope of theaspects is not limited in this respect. In some alternate aspects, theoutput baseband signals 1407 and the input baseband signals 1411 may bedigital baseband signals. In these alternate aspects, the radio ICcircuitry may include analog-to-digital converter (ADC) anddigital-to-analog converter (DAC) circuitry.

In some dual-mode aspects, a separate radio IC circuitry may be providedfor processing signals for each spectrum, or for other spectrums notmentioned here, although the scope of the aspects is not limited in thisrespect.

In some aspects, the synthesizer circuitry 1404 may be a fractional-Nsynthesizer or a fractional N/N+1 synthesizer, although the scope of theaspects is not limited in this respect as other types of frequencysynthesizers may be suitable. For example, synthesizer circuitry 1404may be a delta-sigma synthesizer, a frequency multiplier, or asynthesizer comprising a phase-locked loop with a frequency divider.According to some aspects, the synthesizer circuitry 1404 may includedigital synthesizer circuitry. An advantage of using a digitalsynthesizer circuitry is that, although it may still include some analogcomponents, its footprint may be scaled down much more than thefootprint of an analog synthesizer circuitry. In some aspects, frequencyinput into synthesizer circuity 1404 may be provided by a voltagecontrolled oscillator (VCO), although that is not a requirement. Adivider control input may further be provided by either the basebandprocessing circuitry 1208 (FIG. 12) or the application processor 1211(FIG. 12) depending on the desired output frequency 1405. In someaspects, a divider control input (e.g., N) may be determined from alook-up table (e.g., within a Wi-Fi card) based on a channel number anda channel center frequency as determined or indicated by the applicationprocessor 1211.

In some aspects, synthesizer circuitry 1404 may be configured togenerate a carrier frequency as the output frequency 1405, while inother aspects, the output frequency 1405 may be a fraction of thecarrier frequency (e.g., one-half the carrier frequency, one-third thecarrier frequency). In some aspects, the output frequency 1405 may be aLO frequency (fLO).

FIG. 15 illustrates a functional block diagram of baseband processingcircuitry 1500 in accordance with some aspects. The baseband processingcircuitry 1500 is one example of circuitry that may be suitable for useas the baseband processing circuitry 1208 (FIG. 12), although othercircuitry configurations may also be suitable. The baseband processingcircuitry 1500 may include a receive baseband processor (RX BBP) 1502for processing receive baseband signals 1409 provided by the radio ICcircuitry 1206 (FIG. 12) and a transmit baseband processor (TX BBP) 1504for generating transmit baseband signals 1411 for the radio IC circuitry1206. The baseband processing circuitry 1500 may also include controllogic 1506 for coordinating the operations of the baseband processingcircuitry 1500.

In some aspects (e.g., when analog baseband signals are exchangedbetween the baseband processing circuitry 1500 and the radio ICcircuitry 1206), the baseband processing circuitry 1500 may include ADC1510 to convert analog baseband signals received from the radio ICcircuitry 1206 to digital baseband signals for processing by the RX BBP1502. In these aspects, the baseband processing circuitry 1500 may alsoinclude DAC 1512 to convert digital baseband signals from the TX BBP1504 to analog baseband signals.

In some aspects that communicate OFDM signals or OFDMA signals, such asthrough WLAN baseband circuitry 1208A, the TX BBP 1504 may be configuredto generate OFDM or OFDMA signals as appropriate for transmission byperforming an inverse fast Fourier transform (IFFT). The RX BBP 1502 maybe configured to process received OFDM signals or OFDMA signals byperforming an FFT. In some aspects, the RX BBP 1502 may be configured todetect the presence of an OFDM signal or OFDMA signal by performing anautocorrelation, to detect a preamble, such as a short preamble, and byperforming a cross-correlation, to detect a long preamble. The preamblesmay be part of a predetermined frame structure for Wi-Fi communication.

Referring back to FIG. 12, in some aspects, the antennas 1201 (FIG. 12)may each comprise one or more directional or omnidirectional antennas,including, for example, dipole antennas, monopole antennas, patchantennas, loop antennas, microstrip antennas or other types of antennassuitable for transmission of RF signals. In some multiple-inputmultiple-output (MIMO) aspects, the antennas may be effectivelyseparated to take advantage of spatial diversity and the differentchannel characteristics that may result. Antennas 1201 may each includea set of phased-array antennas, although aspects are not so limited.

Although the radio-architecture 1200 is illustrated as having severalseparate functional elements, one or more of the functional elements maybe combined and may be implemented by combinations ofsoftware-configured elements, such as processing elements includingdigital signal processors (DSPs), or other hardware elements. Forexample, some elements may comprise one or more microprocessors, DSPs,field-programmable gate arrays (FPGAs), application specific integratedcircuits (ASICs), radio-frequency integrated circuits (RFICs) andcombinations of various hardware and logic circuitry for performing atleast the functions described herein. In some aspects, the functionalelements may refer to one or more processes operating on one or moreprocessing elements.

FIG. 16 illustrates a block diagram of an example machine 1600 uponwhich any one or more of the techniques (e.g., methodologies) discussedherein may be performed. In alternative aspects, the machine 1600 mayoperate as a standalone device or may be connected (e.g., networked) toother machines. In a networked deployment, the machine 1600 may operatein the capacity of a server machine, a client machine, or both inserver-client network environments. In an example, the machine 1600 mayact as a peer machine in peer-to-peer (P2P) (or other distributed)network environment. The machine 1600 may be a user equipment (UE),unmanned aerial vehicle (UAV) or other vehicle, evolved Node B (eNB),next generation evolved Node B (gNB), next generation access network(AN), next generation user plane function (UPF), Wi-Fi access point(AP), Wi-Fi station (STA), personal computer (PC), a tablet PC, aset-top box (STB), a personal digital assistant (PDA), a mobiletelephone, a smart phone, a web appliance, a network router, switch orbridge, or any machine capable of executing instructions (sequential orotherwise) that specify actions to be taken by that machine. Further,while only a single machine is illustrated, the term “machine” shallalso be taken to include any collection of machines that individually orjointly execute a set (or multiple sets) of instructions to perform anyone or more of the methodologies discussed herein, such as cloudcomputing, software as a service (SaaS), other computer clusterconfigurations.

Examples, as described herein, may include, or may operate on, logic ora number of components, modules, or mechanisms. Modules are tangibleentities (e.g., hardware) capable of performing specified operations andmay be configured or arranged in a certain manner. In an example,circuits may be arranged (e.g., internally or with respect to externalentities such as other circuits) in a specified manner as a module. Inan example, the whole or part of one or more computer systems (e.g., astandalone, client or server computer system) or one or more hardwareprocessors may be configured by firmware or software (e.g.,instructions, an application portion, or an application) as a modulethat operates to perform specified operations. In an example, thesoftware may reside on a machine-readable medium. In an example, thesoftware, when executed by the underlying hardware of the module, causesthe hardware to perform the specified operations.

Accordingly, the term “module” is understood to encompass a tangibleentity, be that an entity that is physically constructed, specificallyconfigured (e.g., hardwired), or temporarily (e.g., transitorily)configured (e.g., programmed) to operate in a specified manner or toperform part or all of any operation described herein. Consideringexamples in which modules are temporarily configured, each of themodules need not be instantiated at any one moment in time. For example,where the modules comprise a general-purpose hardware processorconfigured using software, the general-purpose hardware processor may beconfigured as respective different modules at different times. Softwaremay accordingly configure a hardware processor, for example, toconstitute a particular module at one instance of time and to constitutea different module at a different instance of time.

Machine (e.g., computer system) 1600 may include a controller 1602(e.g., a hardware processor, a central processing unit (CPU), a graphicsprocessing unit (GPU), a hardware processor core, or any combinationthereof), a main memory 1604 and a static memory 1606, some or all ofwhich may communicate with each other via an interlink (e.g., bus) 1608.The machine 1600 may further include a display unit 1610, analphanumeric input device 1612 (e.g., a keyboard), and a user interface(UI) navigation device 1614 (e.g., a mouse). In an example, the displayunit 1610, input device 1612 and UI navigation device 1614 may be atouch screen display. The machine 1600 may additionally include astorage device (e.g., a drive unit) 1616, a signal generation device1618 (e.g., a speaker), a network interface device 1620, and one or moresensors 1621. The sensors 1621 can include on-board vehicle sensors orother types of vehicle sensors such as speed sensors, etc. The sensors1621 can include sensors capable of detecting location or for utilizinga service for detecting or determining location, such as a globalpositioning system (GPS) sensor, compass, accelerometer, or othersensor. The sensors 1621 can include sensors capable of detectingelevation. The machine 1600 may include an output controller 1632, suchas a serial (e.g., universal serial bus (USB), parallel, or other wiredor wireless (e.g., infrared (IR), near field communication (NFC), etc.)connection to communicate or control one or more peripheral devices(e.g., a printer, card reader, etc.).

The storage device 1616 may include a machine-readable medium 1622 onwhich is stored one or more sets of data structures or instructions 1624(e.g., software) embodying or utilized by any one or more of thetechniques or functions described herein. The instructions 1624 may alsoreside, completely or at least partially, within the main memory 1604,within static memory 1606, or within the controller 1602 duringexecution thereof by the machine 1600. In an example, one or anycombination of the controller 1602, the main memory 1604, the staticmemory 1606, or the storage device 1616 may constitute machine-readablemedia.

While the machine-readable medium 1622 is illustrated as a singlemedium, the term “machine-readable medium” may include a single mediumor multiple media (e.g., a centralized or distributed database, orassociated caches and servers) configured to store the one or moreinstructions 1624.

The term “machine-readable medium” may include any medium that iscapable of storing, encoding, or carrying instructions for execution bythe machine 1600 and that cause the machine 1600 to perform any one ormore of the techniques of the present disclosure, or that is capable ofstoring, encoding or carrying data structures used by or associated withsuch instructions. Non-limiting machine-readable medium examples mayinclude solid-state memories, and optical and magnetic media. Specificexamples of machine-readable media may include: non-volatile memory,such as semiconductor memory devices (e.g., Electrically ProgrammableRead-Only Memory (EPROM), Electrically Erasable Programmable Read-OnlyMemory (EEPROM)) and flash memory devices; magnetic disks, such asinternal hard disks and removable disks; magneto-optical disks; RandomAccess Memory (RAM); and CD-ROM and DVD-ROM disks. In some examples,machine-readable media may include non-transitory machine-readablemedia. In some examples, machine-readable media may includemachine-readable media that is not a transitory propagating signal.

The instructions 1624 may further be transmitted or received over acommunications network 1626 using a transmission medium via the networkinterface device 1620 utilizing any one of a number of transferprotocols (e.g., frame relay, internet protocol (IP), transmissioncontrol protocol (TCP), user datagram protocol (UDP), hypertext transferprotocol (HTTP), etc.). In an example, the network interface device 1620may include a plurality of antennas to wirelessly communicate using atleast one of single-input multiple-output (SIMO), multiple-inputmultiple-output (MIMO), or multiple-input single-output (MISO)techniques. In some examples, the network interface device 1620 maywirelessly communicate using Multiple User MIMO techniques. The term“transmission medium” shall be taken to include any intangible mediumthat is capable of storing, encoding, or carrying instructions forexecution by the machine 1600, and includes digital or analogcommunications signals or other intangible medium to facilitatecommunication of such software.

As used herein, the term “circuitry” may refer to, be part of, orinclude an Application Specific Integrated Circuit (ASIC), an electroniccircuit, a processor (shared, dedicated, or group), or memory (shared,dedicated, or group) that execute one or more software or firmwareprograms, a combinational logic circuit, or other suitable hardwarecomponents that provide the described functionality. In some aspects,the circuitry may be implemented in, or functions associated with thecircuitry may be implemented by, one or more software or firmwaremodules. In some aspects, circuitry may include logic, at leastpartially operable in hardware.

Aspects described herein may be implemented into a system using anysuitably configured hardware or software. FIG. 17 illustrates, for oneaspect, example components of a User Equipment (UE) device 1700. In someaspects, the UE device 1700 may include application circuitry 1702,baseband circuitry 1704, Radio Frequency (RF) circuitry 1706, front-endmodule (FEM) circuitry 1708 and one or more antennas 1710, coupledtogether at least as shown. In some aspects, the UE can be a drone orUAV.

The application circuitry 1702 may include one or more applicationprocessors. For example, the application circuitry 1702 may includecircuitry such as, but not limited to, one or more single-core ormulti-core processors. The processor(s) may include any combination ofgeneral-purpose processors and dedicated processors (e.g., graphicsprocessors, application processors, etc.). The processors may be coupledwith or may include memory/storage and may be configured to executeinstructions stored in the memory/storage to enable various applicationsor operating systems to run on the system.

The baseband circuitry 1704 may include circuitry such as, but notlimited to, one or more single-core or multi-core processors. Thebaseband circuitry 1704 may include one or more baseband processors orcontrol logic to process baseband signals received from a receive signalpath of the RF circuitry 1706 and to generate baseband signals for atransmit signal path of the RF circuitry 1706. Baseband circuity 1704may interface with the application circuitry 1702 for generation andprocessing of the baseband signals and for controlling operations of theRF circuitry 1706. For example, in some aspects, the baseband circuitry1704 may include a second generation (2G) baseband processor 1704A,third generation (3G) baseband processor 1704B, fourth generation (4G)baseband processor 1704C, or other baseband processor(s) 1704D for otherexisting generations, generations in development or to be developed inthe future (e.g., fifth generation (5G), 6G, etc.). The basebandcircuitry 1704 (e.g., one or more of baseband processors 1704A-D) mayhandle various radio control functions that enable communication withone or more radio networks via the RF circuitry 1706. The radio controlfunctions may include, but are not limited to, signalmodulation/demodulation, encoding/decoding, radio frequency shifting,etc. In some aspects, modulation/demodulation circuitry of the basebandcircuitry 1704 may include Fast-Fourier Transform (FFT), precoding, orconstellation mapping/demapping functionality. In some aspects,encoding/decoding circuitry of the baseband circuitry 1704 may includeconvolution, tail-biting convolution, turbo, Viterbi, or Low DensityParity Check (LDPC) encoder/decoder functionality. Aspects ofmodulation/demodulation and encoder/decoder functionality are notlimited to these examples and may include other suitable functionalityin other aspects.

In some aspects, the baseband circuitry 1704 may include elements of aprotocol stack such as, for example, elements of an evolved universalterrestrial radio access network (EUTRAN) protocol including, forexample, physical (PHY), media access control (MAC), radio link control(RLC), packet data convergence protocol (PDCP), or radio resourcecontrol (RRC) elements. A central processing unit (CPU) 1704E of thebaseband circuitry 1704 may be configured to run elements of theprotocol stack for signaling of the PHY, MAC, RLC, PDCP or RRC layers.In some aspects, the baseband circuitry may include one or more audiodigital signal processor(s) (DSP) 1704F. The audio DSP(s) 1704F may beinclude elements for compression/decompression and echo cancellation andmay include other suitable processing elements in other aspects.Components of the baseband circuitry may be suitably combined in asingle chip, a single chipset, or disposed on a same circuit board insome aspects. In some aspects, some or all of the constituent componentsof the baseband circuitry 1704 and the application circuitry 1702 may beimplemented together such as, for example, on a system on a chip (SOC).

In some aspects, the baseband circuitry 1704 may provide forcommunication compatible with one or more radio technologies. Forexample, in some aspects, the baseband circuitry 1704 may supportcommunication with an evolved universal terrestrial radio access network(EUTRAN) or other wireless metropolitan area networks (WMAN), a wirelesslocal area network (WLAN), a wireless personal area network (WPAN).Aspects in which the baseband circuitry 1704 is configured to supportradio communications of more than one wireless protocol may be referredto as multi-mode baseband circuitry.

RF circuitry 1706 may enable communication with wireless networks usingmodulated electromagnetic radiation through a non-solid medium. Invarious aspects, the RF circuitry 1706 may include switches, filters,amplifiers, etc. to facilitate the communication with the wirelessnetwork. RF circuitry 1706 may include a receive signal path which mayinclude circuitry to down-convert RF signals received from the FEMcircuitry 1708 and provide baseband signals to the baseband circuitry1704. RF circuitry 1706 may also include a transmit signal path whichmay include circuitry to up-convert baseband signals provided by thebaseband circuitry 1704 and provide RF output signals to the FEMcircuitry 1708 for transmission.

In some aspects, the RF circuitry 1706 may include a receive signal pathand a transmit signal path. The receive signal path of the RF circuitry1706 may include mixer circuitry 1706A, amplifier circuitry 1706B andfilter circuitry 1706C. The transmit signal path of the RF circuitry1706 may include filter circuitry 1706C and mixer circuitry 1706A. RFcircuitry 1706 may also include synthesizer circuitry 1706D forsynthesizing a frequency for use by the mixer circuitry 1706A of thereceive signal path and the transmit signal path. In some aspects, themixer circuitry 1706A of the receive signal path may be configured todown-convert RF signals received from the FEM circuitry 1708 based onthe synthesized frequency provided by synthesizer circuitry 1706D. Theamplifier circuitry 1706B may be configured to amplify thedown-converted signals and the filter circuitry 1706C may be a low-passfilter (LPF) or band-pass filter (BPF) configured to remove unwantedsignals from the down-converted signals to generate output basebandsignals. Output baseband signals may be provided to the basebandcircuitry 1704 for further processing. In some aspects, the outputbaseband signals may be zero-frequency baseband signals, although thisis not a requirement. In some aspects, mixer circuitry 1706A of thereceive signal path may comprise passive mixers, although the scope ofthe aspects is not limited in this respect.

In some aspects, the mixer circuitry 1706A of the transmit signal pathmay be configured to up-convert input baseband signals based on thesynthesized frequency provided by the synthesizer circuitry 1706D togenerate RF output signals for the FEM circuitry 1708. The basebandsignals may be provided by the baseband circuitry 1704 and may befiltered by filter circuitry 1706C. The filter circuitry 1706C mayinclude a low-pass filter (LPF), although the scope of the aspects isnot limited in this respect.

In some aspects, the mixer circuitry 1706A of the receive signal pathand the mixer circuitry 1706A of the transmit signal path may includetwo or more mixers and may be arranged for quadrature downconversion orupconversion respectively. In some aspects, the mixer circuitry 1706A ofthe receive signal path and the mixer circuitry 1706A of the transmitsignal path may include two or more mixers and may be arranged for imagerejection (e.g., Hartley image rejection). In some aspects, the mixercircuitry 1706A of the receive signal path and the mixer circuitry 1706Aof the transmit signal path may be arranged for direct downconversion ordirect upconversion, respectively. In some aspects, the mixer circuitry1706A of the receive signal path and the mixer circuitry 1706A of thetransmit signal path may be configured for super-heterodyne operation.

In some aspects, the output baseband signals and the input basebandsignals may be analog baseband signals, although the scope of theaspects is not limited in this respect. In some alternate aspects, theoutput baseband signals and the input baseband signals may be digitalbaseband signals. In these alternate aspects, the RF circuitry 1706 mayinclude analog-to-digital converter (ADC) and digital-to-analogconverter (DAC) circuitry and the baseband circuitry 1704 may include adigital baseband interface to communicate with the RF circuitry 1706.

In some dual-mode aspects, a separate radio IC circuitry may be providedfor processing signals for each spectrum, although the scope of theaspects is not limited in this respect.

In some aspects, the synthesizer circuitry 1706D may be a fractional-Nsynthesizer or a fractional N/N+1 synthesizer, although the scope of theaspects is not limited in this respect as other types of frequencysynthesizers may be suitable. For example, synthesizer circuitry 1706Dmay be a delta-sigma synthesizer, a frequency multiplier, or asynthesizer comprising a phase-locked loop with a frequency divider.

The synthesizer circuitry 1706D may be configured to synthesize anoutput frequency for use by the mixer circuitry 1706A of the RFcircuitry 1706 based on a frequency input and a divider control input.In some aspects, the synthesizer circuitry 1706D may be a fractionalN/N+1 synthesizer.

In some aspects, frequency input may be provided by a voltage controlledoscillator (VCO), although that is not a requirement. Divider controlinput may be provided by either the baseband circuitry 1704 or theapplications circuitry 1702 depending on the desired output frequency.In some aspects, a divider control input (e.g., N) may be determinedfrom a look-up table based on a channel indicated by the applicationscircuitry 1702.

Synthesizer circuitry 1706D of the RF circuitry 1706 may include adivider, a delay-locked loop (DLL), a multiplexer and a phaseaccumulator. In some aspects, the divider may be a dual modulus divider(DMD) and the phase accumulator may be a digital phase accumulator(DPA). In some aspects, the DMD may be configured to divide the inputsignal by either N or N+1 (e.g., based on a carry out) to provide afractional division ratio. In some example aspects, the DLL may includea set of cascaded, tunable, delay elements, a phase detector, a chargepump and a D-type flip-flop. In these aspects, the delay elements may beconfigured to break a VCO period up into Nd equal packets of phase,where Nd is the number of delay elements in the delay line. In this way,the DLL provides negative feedback to help ensure that the total delaythrough the delay line is one VCO cycle.

In some aspects, synthesizer circuitry 1706D may be configured togenerate a carrier frequency as the output frequency, while in otheraspects, the output frequency may be a multiple of the carrier frequency(e.g., twice the carrier frequency, four times the carrier frequency)and used in conjunction with quadrature generator and divider circuitryto generate multiple signals at the carrier frequency with multipledifferent phases with respect to each other. In some aspects, the outputfrequency may be a LO frequency (fLO). In some aspects, the RF circuitry1706 may include an IQ/polar converter.

FEM circuitry 1708 may include a receive signal path which may includecircuitry configured to operate on RF signals received from one or moreantennas 1710, amplify the received signals and provide the amplifiedversions of the received signals to the RF circuitry 1706 for furtherprocessing. FEM circuitry 1708 may also include a transmit signal pathwhich may include circuitry configured to amplify signals fortransmission provided by the RF circuitry 1706 for transmission by oneor more of the one or more antennas 1710.

In some aspects, the FEM circuitry 1708 may include a TX/RX switch toswitch between transmit mode and receive mode operation. The FEMcircuitry 1708 may include a receive signal path and a transmit signalpath. The receive signal path of the FEM circuitry 1708 may include alow-noise amplifier (LNA) to amplify received RF signals and provide theamplified received RF signals as an output (e.g., to the RF circuitry1706). The transmit signal path of the FEM circuitry 1708 may include apower amplifier (PA) to amplify input RF signals (e.g., provided by RFcircuitry 1706), and one or more filters to generate RF signals forsubsequent transmission (e.g., by one or more of the one or moreantennas 1710.

In some aspects, the UE device 1700 may include additional elements suchas, for example, memory/storage, display, camera, sensor, orinput/output (I/O) interface.

In Long Term Evolution (LTE) and 5G systems, a mobile terminal (referredto as a User Equipment or UE) connects to the cellular network via abase station (BS), referred to as an evolved Node B or eNB in LTEsystems and as a next generation evolved Node B or gNB in 5G or NRsystems. FIG. 18 illustrates an example of the components of a UE 1804and a base station (e.g., eNB or gNB) 1800. The BS 1800 includesprocessing circuitry 1801 connected to a radio transceiver 1802 forproviding an air interface. The UE 1804 includes processing circuitry1806 connected to a radio transceiver 1808 for providing an airinterface over the wireless medium. Each of the transceivers in thedevices is connected to antennas 1810. The antennas 1810 of the devicesform antenna arrays whose directionality may be controlled by theprocessing circuitry. In examples, the antennas 1810 can be coupled toelectrical or mechanical apparatuses to tilt antennas 1810 towardtargeted cells. In examples, the antennas 1810 can include at least tworeceiving antennas, and the at least two receiving antennas can includeat least one omni-directional antenna and at least one directionalantenna for measuring Reference Signal Received Power (RSRP) or asimilar value. The memory and processing circuitries of the UE or BS maybe configured to perform the functions and implement the schemes of thevarious aspects described herein. The UE can also be configured tooperate as a drone or UAV.

Any of the radio links described herein may operate according to any oneor more of the following radio communication technologies or standardsincluding but not limited to: a Global System for Mobile Communications(GSM) radio communication technology, a General Packet Radio Service(GPRS) radio communication technology, an Enhanced Data Rates for GSMEvolution (EDGE) radio communication technology, or a Third GenerationPartnership Project (3GPP) radio communication technology, for exampleUniversal Mobile Telecommunications System (UMTS), Freedom of MultimediaAccess (FOMA), 3GPP Long Term Evolution (LTE), 3GPP Long Term EvolutionAdvanced (LTE Advanced), Code division multiple access 2000 (CDMA2000),Cellular Digital Packet Data (CDPD), Mobitex, Third Generation (3G),Circuit Switched Data (CSD), High-Speed Circuit-Switched Data (HSCSD),Universal Mobile Telecommunications System (Third Generation) (UMTS(3G)), Wideband Code Division Multiple Access (Universal MobileTelecommunications System) (W-CDMA (UMTS)), High Speed Packet Access(HSPA), High-Speed Downlink Packet Access (HSDPA), High-Speed UplinkPacket Access (HSUPA), High Speed Packet Access Plus (HSPA+), UniversalMobile Telecommunications System-Time-Division Duplex (UMTS-TDD), TimeDivision-Code Division Multiple Access (TD-CDMA), TimeDivision-Synchronous Code Division Multiple Access (TD-CDMA), 3rdGeneration Partnership Project Release 8 (Pre-4th Generation) (3GPP Rel.8 (Pre-4G)), 3GPP Rel. 9 (3rd Generation Partnership Project Release 9),3GPP Rel. 10 (3rd Generation Partnership Project Release 10) , 3GPP Rel.11 (3rd Generation Partnership Project Release 11), 3GPP Rel. 12 (3rdGeneration Partnership Project Release 12), 3GPP Rel. 13 (3rd GenerationPartnership Project Release 13), 3GPP Rel. 14 (3rd GenerationPartnership Project Release 14), 3GPP Rel. 15 (3rd GenerationPartnership Project Release 15), 3GPP Rel. 16 (3rd GenerationPartnership Project Release 16), 3GPP Rel. 17 (3rd GenerationPartnership Project Release 17) and subsequent Releases (such as Rel.18, Rel. 19, etc.), 3GPP 5G, 3GPP LTE Extra, LTE-Advanced Pro, LTELicensed-Assisted Access (LAA), MuLTEfire, UMTS Terrestrial Radio Access(UTRA), Evolved UMTS Terrestrial Radio Access (E-UTRA), Long TermEvolution Advanced (4th Generation) (LTE Advanced (4G)), cdmaOne (2G),Code division multiple access 2000 (Third generation) (CDMA2000 (3G)),Evolution-Data Optimized or Evolution-Data Only (EV-DO), Advanced MobilePhone System (1st Generation) (AMPS (1G)), Total Access CommunicationSystem/Extended Total Access Communication System (TACS/ETACS), DigitalAMPS (2nd Generation) (D-AMPS (2G)), Push-to-talk (PTT), MobileTelephone System (MTS), Improved Mobile Telephone System (IMTS),Advanced Mobile Telephone System (AMTS), OLT (Norwegian for OffentligLandmobil Telefoni, Public Land Mobile Telephony), MTD (Swedishabbreviation for Mobiltelefonisystem D, or Mobile telephony system D),Public Automated Land Mobile (Autotel/PALM), ARP (Finnish forAutoradiopuhelin, “car radio phone”), NMT (Nordic Mobile Telephony),High capacity version of NTT (Nippon Telegraph and Telephone) (Hicap),Cellular Digital Packet Data (CDPD), Mobitex, DataTAC, IntegratedDigital Enhanced Network (iDEN), Personal Digital Cellular (PDC),Circuit Switched Data (CSD), Personal Handy-phone System (PHS), WidebandIntegrated Digital Enhanced Network (WiDEN), iBurst, Unlicensed MobileAccess (UMA), also referred to as also referred to as 3GPP GenericAccess Network, or GAN standard), Zigbee, Bluetooth®, Wireless GigabitAlliance (WiGig) standard, mmWave standards in general (wireless systemsoperating at 10-300 GHz and above such as WiGig, IEEE 802.11ad, IEEE802.11ay, etc.), technologies operating above 300 GHz and THz bands,(3GPP/LTE based or IEEE 802.11p and other) Vehicle-to-Vehicle (V2V) andVehicle-to-X (V2X) and Vehicle-to-Infrastructure (V2I) andInfrastructure-to-Vehicle (I2V) communication technologies, 3GPPcellular V2X, DSRC (Dedicated Short Range Communications) communicationsystems such as Intelligent-Transport-Systems and others (typicallyoperating in 5850 MHz to 5925 MHz), the European ITS-G5 system (i.e. theEuropean flavor of IEEE 802.11p based DSRC, including ITS-G5A (i.e.,Operation of ITS-G5 in European ITS frequency bands dedicated to ITS forsafety related applications in the frequency range 5,875 GHz to 5,905GHz), ITS-G5B (i.e., Operation in European ITS frequency bands dedicatedto ITS non-safety applications in the frequency range 5,855 GHz to 5,875GHz), ITS -G5C (i.e., Operation of ITS applications in the frequencyrange 5,470 GHz to 5,725 GHz)), DSRC in Japan in the 700 MHz band(including 715 MHz to 725 MHz) etc.

Aspects described herein can be used in the context of any spectrummanagement scheme including dedicated licensed spectrum, unlicensedspectrum, (licensed) shared spectrum (such as LSA=Licensed Shared Accessin 2.3-2.4 GHz, 3.4-3.6 GHz, 3.6-3.8 GHz and further frequencies andSAS=Spectrum Access System/CBRS=Citizen Broadband Radio System in3.55-3.7 GHz and further frequencies). Applicable spectrum bands includeIMT (International Mobile Telecommunications) spectrum as well as othertypes of spectrum/bands, such as bands with national allocation.

To better illustrate the method and apparatuses disclosed herein, anon-limiting list of embodiments is provided here.

Example 1 is an autonomous vehicle distributed services systemcomprising: a content delivery network device to receive a servicescontent data set from a cloud device; and a mobile edge computing deviceto: receive the services content data set from the content deliverynetwork device; generate a services advertisement data set based on theservices content data set; and provide service access to an autonomousvehicle based on the services advertisement data set.

In Example 2, the subject matter of Example 1 optionally includeswherein the services content data set includes at least one of a highdefinition vehicle navigation data set, a smart parking service dataset, a vehicle software update data set, a vehicle firmware update dataset, a vehicle security patch data set, a location-based traffic dataset, a location-based weather data set, an entertainment service dataset, and an office service data set.

In Example 3, the subject matter of any one or more of Examples 1-2optionally include a roadside unit to: receive the servicesadvertisement data set from the mobile edge computing device; andreceive a services subscription data set from the autonomous vehicle,wherein the provision of the service access is based on the servicessubscription data set.

In Example 4, the subject matter of Example 3 optionally includeswherein the mobile edge computing device is further configured to:provide the generated services advertisement data set to the autonomousvehicle; and receive the services subscription data set from theautonomous vehicle, wherein the provision of the service access is basedon the services subscription data set.

In Example 5, the subject matter of any one or more of Examples 3-4optionally include an edge node device to: provide the servicesadvertisement data set to the autonomous vehicle; receive the servicessubscription data set from the autonomous vehicle; and authenticate aservice access for the autonomous vehicle based on the servicessubscription data set.

In Example 6, the subject matter of any one or more of Examples 3-5optionally include wherein the roadside unit is further configured to:provide the services advertisement data set to the autonomous vehicle;receive the services subscription data set from the autonomous vehicle;and authenticate the service access for the autonomous vehicle based onthe services subscription data set.

In Example 7, the subject matter of any one or more of Examples 3-6optionally include wherein the roadside unit is further configured to:provide a vehicle authentication request from the roadside unit to thecloud device; and receive a vehicle authentication verification, whereinthe provision of the service access is based on the vehicleauthentication verification.

In Example 8, the subject matter of any one or more of Examples 5-7optionally include wherein the edge node device is further configuredto: provide the vehicle authentication request from the edge node deviceto the cloud device; and receive the vehicle authenticationverification, wherein the provision of the service access includessending a plurality of service data, the plurality of service dataencrypted based on the vehicle authentication verification.

In Example 9, the subject matter of any one or more of Examples 1-8optionally include wherein: the cloud device provides a one-timedecryption key to the autonomous vehicle; the edge node devicecommunicates with the autonomous vehicle based on messages encryptedbased on a one-time encryption key, the one-time decryption keyproviding decryption of messages encrypted using the one-time encryptionkey; and the roadside unit communicates with the autonomous vehiclebased on messages encrypted based on the one-time encryption key.

Example 10 is an autonomous vehicle distributed services methodcomprising: receiving a services content data set at a content deliverynetwork device from a cloud device; receiving the services content dataset at a mobile edge computing device from the content delivery networkdevice; generating a services advertisement data set based on theservices content data set; and providing service access to an autonomousvehicle based on the services advertisement data set.

In Example 11, the subject matter of Example 10 optionally includesreceiving the services advertisement data set at a roadside unit fromthe mobile edge computing device; and receiving a services subscriptiondata set from the autonomous vehicle at the roadside unit, wherein theprovision of the service access is based on the services subscriptiondata set.

In Example 12, the subject matter of Example 11 optionally includesproviding the generated services advertisement data set to theautonomous vehicle; and receiving the services subscription data setfrom the autonomous vehicle, wherein the provision of the service accessis based on the services subscription data set.

In Example 13, the subject matter of any one or more of Examples 11-12optionally include providing the services advertisement data set from anedge node device to the autonomous vehicle; receiving the servicessubscription data set from the autonomous vehicle; and authenticating aservice access for the autonomous vehicle based on the servicessubscription data set.

In Example 14, the subject matter of any one or more of Examples 11-13optionally include providing the services advertisement data set to theautonomous vehicle; receiving the services subscription data set fromthe autonomous vehicle; and authenticating the service access for theautonomous vehicle based on the services subscription data set.

In Example 15, the subject matter of any one or more of Examples 11-14optionally include providing a vehicle authentication request from theroadside unit to the cloud device; and receiving a vehicleauthentication verification, wherein the provision of the service accessis based on the vehicle authentication verification.

In Example 16, the subject matter of any one or more of Examples 13-15optionally include providing the vehicle authentication request from theedge node device to the cloud device; and receiving the vehicleauthentication verification, wherein the provision of the service accessincludes sending a plurality of service data, the plurality of servicedata encrypted based on the vehicle authentication verification.

In Example 17, the subject matter of any one or more of Examples 10-16optionally include providing a one-time decryption key from the clouddevice to the autonomous vehicle; wherein: the edge node devicecommunicates with the autonomous vehicle based on messages encryptedbased on a one-time encryption key, the one-time decryption keyproviding decryption of messages encrypted using the one-time encryptionkey; and the roadside unit communicates with the autonomous vehiclebased on messages encrypted based on the one-time encryption key.

Example 18 is at least one machine-readable medium includinginstructions, which when executed by a computing system, cause thecomputing system to perform any of the methods of Examples 10-17.

Example 19 is an apparatus comprising means for performing any of themethods of Examples 10-17.

Example 20 is at least one non-transitory machine-readable storagemedium, comprising a plurality of instructions that, responsive to beingexecuted with processor circuitry of a computer-controlled device, causethe computer-controlled device to: receive a services content data setat a content delivery network device from a cloud device; receive theservices content data set at a mobile edge computing device from thecontent delivery network device; generate a services advertisement dataset based on the services content data set; and provide service accessto an autonomous vehicle based on the services advertisement data set.

In Example 21, the subject matter of Example 20 optionally includes theinstructions further causing the computer-controlled device to: receivethe services advertisement data set at a roadside unit from the mobileedge computing device; and receive a services subscription data set fromthe autonomous vehicle at the roadside unit, wherein the provision ofthe service access is based on the services subscription data set.

In Example 22, the subject matter of Example 21 optionally includes theinstructions further causing the computer-controlled device to: providethe generated services advertisement data set to the autonomous vehicle;and receive the services subscription data set from the autonomousvehicle, wherein the provision of the service access is based on theservices subscription data set.

In Example 23, the subject matter of any one or more of Examples 21-22optionally include the instructions further causing thecomputer-controlled device to: provide the services advertisement dataset from an edge node device to the autonomous vehicle; receive theservices subscription data set from the autonomous vehicle; andauthenticate a service access for the autonomous vehicle based on theservices subscription data set.

In Example 24, the subject matter of any one or more of Examples 21-23optionally include the instructions further causing thecomputer-controlled device to: provide the services advertisement dataset to the autonomous vehicle; receive the services subscription dataset from the autonomous vehicle; and authenticate the service access forthe autonomous vehicle based on the services subscription data set.

In Example 25, the subject matter of any one or more of Examples 21-24optionally include the instructions further causing thecomputer-controlled device to: provide a vehicle authentication requestfrom the roadside unit to the cloud device; and receive a vehicleauthentication verification, wherein the provision of the service accessis based on the vehicle authentication verification.

In Example 26, the subject matter of any one or more of Examples 23-25optionally include the instructions further causing thecomputer-controlled device to: provide the vehicle authenticationrequest from the edge node device to the cloud device; and receive thevehicle authentication verification, wherein the provision of theservice access includes sending a plurality of service data, theplurality of service data encrypted based on the vehicle authenticationverification.

In Example 27, the subject matter of any one or more of Examples 20-26optionally include the instructions further causing thecomputer-controlled device to provide a one-time decryption key from thecloud device to the autonomous vehicle; wherein: the edge node devicecommunicates with the autonomous vehicle based on messages encryptedbased on a one-time encryption key, the one-time decryption keyproviding decryption of messages encrypted using the one-time encryptionkey; and the roadside unit communicates with the autonomous vehiclebased on messages encrypted based on the one-time encryption key.

Example 28 is an autonomous vehicle distributed services apparatuscomprising: means for receiving a services content data set at a contentdelivery network device from a cloud device; means for receiving theservices content data set at a mobile edge computing device from thecontent delivery network device; means for generating a servicesadvertisement data set based on the services content data set; and meansfor providing service access to an autonomous vehicle based on theservices advertisement data set.

In Example 29, the subject matter of Example 28 optionally includesmeans for receiving the services advertisement data set at a roadsideunit from the mobile edge computing device; and means for receiving aservices subscription data set from the autonomous vehicle at theroadside unit, wherein the provision of the service access is based onthe services subscription data set.

In Example 30, the subject matter of Example 29 optionally includesmeans for providing the generated services advertisement data set to theautonomous vehicle; and means for receiving the services subscriptiondata set from the autonomous vehicle, wherein the provision of theservice access is based on the services subscription data set.

In Example 31, the subject matter of any one or more of Examples 29-30optionally include means for providing the services advertisement dataset from an edge node device to the autonomous vehicle; means forreceiving the services subscription data set from the autonomousvehicle; and means for authenticating a service access for theautonomous vehicle based on the services subscription data set.

In Example 32, the subject matter of any one or more of Examples 29-31optionally include means for providing the services advertisement dataset to the autonomous vehicle; means for receiving the servicessubscription data set from the autonomous vehicle; and means forauthenticating the service access for the autonomous vehicle based onthe services subscription data set.

In Example 33, the subject matter of any one or more of Examples 29-32optionally include means for providing a vehicle authentication requestfrom the roadside unit to the cloud device; and means for receiving avehicle authentication verification, wherein the provision of theservice access is based on the vehicle authentication verification.

In Example 34, the subject matter of any one or more of Examples 31-33optionally include means for providing the vehicle authenticationrequest from the edge node device to the cloud device; and means forreceiving the vehicle authentication verification, wherein the provisionof the service access includes sending a plurality of service data, theplurality of service data encrypted based on the vehicle authenticationverification.

In Example 35, the subject matter of any one or more of Examples 28-34optionally include means for providing a one-time decryption key fromthe cloud device to the autonomous vehicle; wherein: the edge nodedevice communicates with the autonomous vehicle based on messagesencrypted based on a one-time encryption key, the one-time decryptionkey providing decryption of messages encrypted using the one-timeencryption key; and the roadside unit communicates with the autonomousvehicle based on messages encrypted based on the one-time encryptionkey.

Example 36 is a quality of service predictive system comprising: anapplication server to receive a plurality of network parameters andgenerate a plurality of vehicle service application information; and aquality of experience device to: receive a plurality of quality ofexperience measurements from a plurality of remote devices; generate theplurality of network parameters based on the plurality of quality ofexperience measurements; receive the plurality of vehicle serviceapplication information from the application server; and generate avehicle wireless communication quality of service data set based on theplurality of vehicle service application information and the pluralityof quality of experience measurements.

In Example 37, the subject matter of Example 36 optionally includes thequality of experience device further to receive a plurality of vehicleservice application information from a vehicle, wherein the generationof the vehicle wireless communication quality of service data set isfurther based on the plurality of vehicle service applicationinformation.

In Example 38, the subject matter of Example 37 optionally includeswherein the vehicle includes the quality of experience device.

In Example 39, the subject matter of any one or more of Examples 36-38optionally include wherein the generation of the vehicle wirelesscommunication quality of service data set includes: training a machinelearning model based on the plurality of quality of experiencemeasurements; and generating the vehicle wireless communication qualityof service data set based on the trained machine learning model.

In Example 40, the subject matter of any one or more of Examples 36-39optionally include wherein the plurality of remote devices includes aplurality of remote vehicles.

In Example 41, the subject matter of any one or more of Examples 36-40optionally include wherein: the quality of experience device includes anetwork reconfiguration device to receive a network reconfigurationinput; and the generation of the vehicle wireless communication qualityof service data set is further based on the network reconfigurationinput.

In Example 42, the subject matter of Example 41 optionally includeswherein the network reconfiguration device generates a network trafficanalysis output based on the network reconfiguration input.

In Example 43, the subject matter of Example 42 optionally includeswherein the generation of the network traffic analysis output includesat least one of deep packet inspection and intelligent network trafficclassification.

Example 44 is a quality of service predictive method comprising:receiving a plurality of network parameters at an application server;generating a plurality of vehicle service application information at theapplication server; receiving a plurality of quality of experiencemeasurements at a quality of experience device from a plurality ofremote devices; generating the plurality of network parameters based onthe plurality of quality of experience measurements; receiving theplurality of vehicle service application information from theapplication server; and generating a vehicle wireless communicationquality of service data set based on the plurality of vehicle serviceapplication information and the plurality of quality of experiencemeasurements.

In Example 45, the subject matter of Example 44 optionally includesreceiving a plurality of vehicle service application information from avehicle, wherein the generation of the vehicle wireless communicationquality of service data set is further based on the plurality of vehicleservice application information.

In Example 46, the subject matter of Example 45 optionally includeswherein the vehicle includes the quality of experience device.

In Example 47, the subject matter of any one or more of Examples 44-46optionally include wherein the generation of the vehicle wirelesscommunication quality of service data set includes: training a machinelearning model based on the plurality of quality of experiencemeasurements; and generating the vehicle wireless communication qualityof service data set based on the trained machine learning model.

In Example 48, the subject matter of any one or more of Examples 44-47optionally include wherein the plurality of remote devices includes aplurality of remote vehicles.

In Example 49, the subject matter of any one or more of Examples 44-48optionally include wherein: the quality of experience device includes anetwork reconfiguration device to receive a network reconfigurationinput; and the generation of the vehicle wireless communication qualityof service data set is further based on the network reconfigurationinput.

In Example 50, the subject matter of Example 49 optionally includeswherein the network reconfiguration device generates a network trafficanalysis output based on the network reconfiguration input.

In Example 51, the subject matter of Example 50 optionally includeswherein the generation of the network traffic analysis output includesat least one of deep packet inspection and intelligent network trafficclassification.

Example 52 is at least one machine-readable medium includinginstructions, which when executed by a computing system, cause thecomputing system to perform any of the methods of Examples 44-51.

Example 53 is an apparatus comprising means for performing any of themethods of Examples 44-51.

Example 54 is at least one non-transitory machine-readable storagemedium, comprising a plurality of instructions that, responsive to beingexecuted with processor circuitry of a computer-controlled device, causethe computer-controlled device to: receive a plurality of networkparameters at an application server; generate a plurality of vehicleservice application information at the application server; receive aplurality of quality of experience measurements at a quality ofexperience device from a plurality of remote devices; generate theplurality of network parameters based on the plurality of quality ofexperience measurements; receive the plurality of vehicle serviceapplication information from the application server; and generate avehicle wireless communication quality of service data set based on theplurality of vehicle service application information and the pluralityof quality of experience measurements.

In Example 55, the subject matter of Example 54 optionally includes theinstructions further causing the computer-controlled device to receive aplurality of vehicle service application information from a vehicle,wherein the generation of the vehicle wireless communication quality ofservice data set is further based on the plurality of vehicle serviceapplication information.

In Example 56, the subject matter of Example 55 optionally includeswherein the vehicle includes the quality of experience device.

In Example 57, the subject matter of any one or more of Examples 54-56optionally include the instructions further causing thecomputer-controlled device to train a machine learning model based onthe plurality of quality of experience measurements; and generate thevehicle wireless communication quality of service data set based on thetrained machine learning model.

In Example 58, the subject matter of any one or more of Examples 54-57optionally include wherein the plurality of remote devices includes aplurality of remote vehicles.

In Example 59, the subject matter of any one or more of Examples 54-58optionally include wherein: the quality of experience device includes anetwork reconfiguration device to receive a network reconfigurationinput; and the generation of the vehicle wireless communication qualityof service data set is further based on the network reconfigurationinput.

Example 60 is a quality of service predictive apparatus comprising:means for receiving a plurality of network parameters at an applicationserver; means for generating a plurality of vehicle service applicationinformation at the application server; means for receiving a pluralityof quality of experience measurements at a quality of experience devicefrom a plurality of remote devices; means for generating the pluralityof network parameters based on the plurality of quality of experiencemeasurements; means for receiving the plurality of vehicle serviceapplication information from the application server; and means forgenerating a vehicle wireless communication quality of service data setbased on the plurality of vehicle service application information andthe plurality of quality of experience measurements.

In Example 61, the subject matter of Example 60 optionally includesmeans for receiving a plurality of vehicle service applicationinformation from a vehicle, wherein the generation of the vehiclewireless communication quality of service data set is further based onthe plurality of vehicle service application information.

In Example 62, the subject matter of Example 61 optionally includeswherein the vehicle includes the quality of experience device.

In Example 63, the subject matter of any one or more of Examples 60-62optionally include wherein the generation of the vehicle wirelesscommunication quality of service data set includes: means for training amachine learning model based on the plurality of quality of experiencemeasurements; and means for generating the vehicle wirelesscommunication quality of service data set based on the trained machinelearning model.

In Example 64, the subject matter of any one or more of Examples 60-63optionally include wherein the plurality of remote devices includes aplurality of remote vehicles.

In Example 65, the subject matter of any one or more of Examples 60-64optionally include wherein: the quality of experience device includes anetwork reconfiguration device to receive a network reconfigurationinput; and the generation of the vehicle wireless communication qualityof service data set is further based on the network reconfigurationinput.

Example 66 is an optical wireless communication system comprising: anoptical transducer to transduce an input signal into an optical signal;and an optical wireless communication lens to focus the optical signalonto an area of substantially uniform light intensity.

In Example 67, the subject matter of Example 66 optionally includeswherein the optical wireless communication lens is configured to focusthe optical signal onto a vehicle area.

In Example 68, the subject matter of Example 67 optionally includeswherein the vehicle area includes an average vehicle distance and avehicle distance range.

In Example 69, the subject matter of any one or more of Examples 67-68optionally include wherein the vehicle area includes a substantiallyelliptical area that is longer in a vehicle travel direction andnarrower perpendicular to a vehicle travel direction.

In Example 70, the subject matter of any one or more of Examples 66-69optionally include an optical wireless communication receiver to receivea return transmission.

In Example 71, the subject matter of any one or more of Examples 66-70optionally include a vehicular optical receiver to receive the focusedoptical signal.

In Example 72, the subject matter of Example 71 optionally includeswherein the vehicular optical receiver includes a plurality of opticaldetectors.

In Example 73, the subject matter of any one or more of Examples 71-72optionally include wherein the vehicular optical receiver includes amechanical actuator to adjust at least a portion of the vehicularoptical receiver to improve the reception of the focused optical signal.

Example 74 is an optical wireless communication method comprising:transducing an input signal at an optical transducer into an opticalsignal; and focusing the optical signal at an optical wirelesscommunication lens onto an area of substantially uniform lightintensity.

In Example 75, the subject matter of Example 74 optionally includeswherein the optical wireless communication lens is configured to focusthe optical signal onto a vehicle area.

In Example 76, the subject matter of Example 75 optionally includeswherein the vehicle area includes an average vehicle distance and avehicle distance range.

In Example 77, the subject matter of any one or more of Examples 75-76optionally include wherein the vehicle area includes a substantiallyelliptical area that is longer in a vehicle travel direction andnarrower perpendicular to a vehicle travel direction.

In Example 78, the subject matter of any one or more of Examples 74-77optionally include receiving a return transmission at an opticalwireless communication receiver.

In Example 79, the subject matter of any one or more of Examples 74-78optionally include receiving the focused optical signal at a vehicularoptical receiver.

In Example 80, the subject matter of Example 79 optionally includeswherein the vehicular optical receiver includes a plurality of opticaldetectors.

In Example 81, the subject matter of any one or more of Examples 79-80optionally include wherein the vehicular optical receiver includes amechanical actuator to adjust at least a portion of the vehicularoptical receiver to improve the reception of the focused optical signal.

Example 82 is at least one machine-readable medium includinginstructions, which when executed by a computing system, cause thecomputing system to perform any of the methods of Examples 74-81.

Example 83 is an apparatus comprising means for performing any of themethods of Examples 74-81.

Example 84 is at least one non-transitory machine-readable storagemedium, comprising a plurality of instructions that, responsive to beingexecuted with processor circuitry of a computer-controlled device, causethe computer-controlled device to: transduce an input signal at anoptical transducer into an optical signal; and focus the optical signalat an optical wireless communication lens onto an area of substantiallyuniform light intensity.

In Example 85, the subject matter of Example 84 optionally includeswherein the optical wireless communication lens is configured to focusthe optical signal onto a vehicle area.

In Example 86, the subject matter of Example 85 optionally includeswherein the vehicle area includes an average vehicle distance and avehicle distance range.

In Example 87, the subject matter of any one or more of Examples 85-86optionally include wherein the vehicle area includes a substantiallyelliptical area that is longer in a vehicle travel direction andnarrower perpendicular to a vehicle travel direction.

In Example 88, the subject matter of any one or more of Examples 84-87optionally include the instructions further causing thecomputer-controlled device to receive a return transmission at anoptical wireless communication receiver.

In Example 89, the subject matter of any one or more of Examples 84-88optionally include the instructions further causing thecomputer-controlled device to receive the focused optical signal at avehicular optical receiver.

In Example 90, the subject matter of Example 89 optionally includeswherein the vehicular optical receiver includes a plurality of opticaldetectors.

In Example 91, the subject matter of any one or more of Examples 89-90optionally include wherein the vehicular optical receiver includes amechanical actuator to adjust at least a portion of the vehicularoptical receiver to improve the reception of the focused optical signal.

Example 92 is an optical wireless communication apparatus comprising:means for transducing an input signal at an optical transducer into anoptical signal; and means for focusing the optical signal at an opticalwireless communication lens onto an area of substantially uniform lightintensity.

In Example 93, the subject matter of Example 92 optionally includeswherein the optical wireless communication lens is configured to focusthe optical signal onto a vehicle area.

In Example 94, the subject matter of Example 93 optionally includeswherein the vehicle area includes an average vehicle distance and avehicle distance range.

In Example 95, the subject matter of any one or more of Examples 93-94optionally include wherein the vehicle area includes a substantiallyelliptical area that is longer in a vehicle travel direction andnarrower perpendicular to a vehicle travel direction.

In Example 96, the subject matter of any one or more of Examples 92-95optionally include means for receiving a return transmission at anoptical wireless communication receiver.

In Example 97, the subject matter of any one or more of Examples 92-96optionally include means for receiving the focused optical signal at avehicular optical receiver.

In Example 98, the subject matter of Example 97 optionally includeswherein the vehicular optical receiver includes a plurality of opticaldetectors.

In Example 99, the subject matter of any one or more of Examples 97-98optionally include wherein the vehicular optical receiver includes amechanical actuator to adjust at least a portion of the vehicularoptical receiver to improve the reception of the focused optical signal.

Example 100 is at least one machine-readable medium includinginstructions, which when executed by a machine, cause the machine toperform operations of any of the operations of Examples 1-99.

Example 101 is an apparatus comprising means for performing any of theoperations of Examples 1-99.

Example 102 is a system to perform the operations of any of the Examples1-99.

Example 103 is a method to perform the operations of any of the Examples1-99.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) may be used in combination with each other. Otheraspects can be used, such as by one of ordinary skill in the art uponreviewing the above description. Also, in the above DetailedDescription, various features may be grouped together to streamline thedisclosure. This should not be interpreted as intending that anunclaimed disclosed feature is essential to any claim. Rather, inventivesubject matter may lie in less than all features of a particulardisclosed aspect. Thus, the following claims are hereby incorporatedinto the Detailed Description, with each claim standing on its own as aseparate aspect. The scope of various aspects of the disclosure can bedetermined with reference to the appended claims, along with the fullscope of equivalents to which such claims are entitled.

In this document, the terms “a” or “an” are used, as is common in patentdocuments, to include one or more than one, independent of any otherinstances or usages of “at least one” or “one or more.” In thisdocument, the term “or” is used to refer to a nonexclusive or, such that“A or B” includes “A but not B,” “B but not A,” and “A and B,” unlessotherwise indicated. In the appended claims, the terms “including” and“in which” are used as the plain-English equivalents of the respectiveterms “comprising” and “wherein.” Also, in the following claims, theterms “including” and “comprising” are open-ended, that is, a system,device, article, or process that includes elements in addition to thoselisted after such a term in a claim are still deemed to fall within thescope of that claim. Moreover, in the following claims, the terms“first,” “second,” and “third,” etc. are used merely as labels, and arenot intended to impose numerical requirements on their objects.

The Abstract is provided to comply with 37 C.F.R. Section 1.72(b)requiring an abstract that will allow the reader to ascertain the natureand gist of the technical disclosure. It is submitted with theunderstanding that it will not be used to limit or interpret the scopeor meaning of the claims. The following claims are hereby incorporatedinto the detailed description, with each claim standing on its own as aseparate aspect.

The above description is intended to be illustrative, and notrestrictive. For example, the above-described examples (or one or moreaspects thereof) may be used in combination with others. Other aspectsmay be used, such as by one of ordinary skill in the art upon reviewingthe above description. The Abstract is to allow the reader to quicklyascertain the nature of the technical disclosure. It is submitted withthe understanding that it will not be used to interpret or limit thescope or meaning of the claims. Also, in the above Detailed Description,various features may be grouped together to streamline the disclosure.However, the claims may not set forth every feature disclosed herein asaspects may feature a subset of said features. Further, aspects mayinclude fewer features than those disclosed in a particular example.Thus, the following claims are hereby incorporated into the DetailedDescription, with a claim standing on its own as a separate aspect. Thescope of the aspects disclosed herein is to be determined with referenceto the appended claims, along with the full scope of equivalents towhich such claims are entitled.

1. An autonomous vehicle distributed services system comprising: acontent delivery network device to receive a services content data setfrom a cloud device; and a mobile edge computing device to: receive theservices content data set from the content delivery network device;generate a services advertisement data set based on the services contentdata set; and provide service access to an autonomous vehicle based onthe services advertisement data set.
 2. The system of claim 1, whereinthe services content data set includes at least one of a high definitionvehicle navigation data set, a smart parking service data set, a vehiclesoftware update data set, a vehicle firmware update data set, a vehiclesecurity patch data set, a location-based traffic data set, alocation-based weather data set, an entertainment service data set, andan office service data set.
 3. The system of claim 1, further includinga roadside unit to: receive the services advertisement data set from themobile edge computing device; and receive a services subscription dataset from the autonomous vehicle, wherein the provision of the serviceaccess is based on the services subscription data set.
 4. The system ofclaim 3, wherein the mobile edge computing device is further configuredto: provide the generated services advertisement data set to theautonomous vehicle; and receive the services subscription data set fromthe autonomous vehicle, wherein the provision of the service access isbased on the services subscription data set.
 5. The system of claim 3,further including an edge node device to: provide the servicesadvertisement data set to the autonomous vehicle; receive the servicessubscription data set from the autonomous vehicle; and authenticate aservice access for the autonomous vehicle based on the servicessubscription data set.
 6. The system of claim 3, wherein the roadsideunit is further configured to: provide the services advertisement dataset to the autonomous vehicle; receive the services subscription dataset from the autonomous vehicle; and authenticate the service access forthe autonomous vehicle based on the services subscription data set. 7.The system of claim 3, wherein the roadside unit is further configuredto: provide a vehicle authentication request from the roadside unit tothe cloud device; and receive a vehicle authentication verification,wherein the provision of the service access is based on the vehicleauthentication verification.
 8. The system of claim 5, wherein the edgenode device is further configured to: provide the vehicle authenticationrequest from the edge node device to the cloud device; and receive thevehicle authentication verification, wherein the provision of theservice access includes sending a plurality of service data, theplurality of service data encrypted based on the vehicle authenticationverification.
 9. The system of claim 1, wherein: the cloud deviceprovides a one-time decryption key to the autonomous vehicle; the edgenode device communicates with the autonomous vehicle based on messagesencrypted based on a one-time encryption key, the one-time decryptionkey providing decryption of messages encrypted using the one-timeencryption key; and the roadside unit communicates with the autonomousvehicle based on messages encrypted based on the one-time encryptionkey. 10-25. (canceled)
 26. A mobile edge computing device comprising: amemory storing software instructions; and processing circuitryconfigured to execute the software instructions to cause the mobile edgecomputing device to: receive, from a content delivery network device, aservices content data set; generate a services advertisement data setbased on the services content data set; and provide service access to anautonomous vehicle based on the services advertisement data set.
 27. Themobile edge computing device of claim 26, wherein the services contentdata set includes at least one of a high definition vehicle navigationdata set, a smart parking service data set, a vehicle software updatedata set, a vehicle firmware update data set, a vehicle security patchdata set, a location-based traffic data set, a location-based weatherdata set, an entertainment service data set, and an office service dataset.
 28. The mobile edge computing device of claim 26, wherein theprocessing circuitry is further configured to execute the softwareinstructions to cause the mobile edge computing device to provide theservices advertisement data set to a roadside unit.
 29. The mobile edgecomputing device of claim 26, wherein the processing circuitry isfurther configured to execute the software instructions to cause themobile edge computing device to: provide the generated servicesadvertisement data set to the autonomous vehicle; and receive a servicessubscription data set from the autonomous vehicle, wherein the provisionof the service access is based on the services subscription data set.30. The mobile edge computing device of claim 26, wherein the processingcircuitry is further configured to execute the software instructions tocause the mobile edge computing device to provide network-based cachingof content for services from a plurality of content delivery networkproviders.
 31. The mobile edge computing device of claim 26, wherein themobile edge computing device is associated with a cellular base station.32. A non-transitory computer-readable memory medium storing softwareinstructions executable by a processor of a mobile edge computing deviceto cause the mobile edge computing device to: receive, from a contentdelivery network device, a services content data set; generate aservices advertisement data set based on the services content data set;and provide service access to an autonomous vehicle based on theservices advertisement data set.
 33. The non-transitorycomputer-readable memory medium of claim 32, wherein the servicescontent data set includes at least one of a high definition vehiclenavigation data set, a smart parking service data set, a vehiclesoftware update data set, a vehicle firmware update data set, a vehiclesecurity patch data set, a location-based traffic data set, alocation-based weather data set, an entertainment service data set, andan office service data set.
 34. The non-transitory computer-readablememory medium of claim 32, wherein the software instructions are furtherexecutable to cause the mobile edge computing device to provide theservices advertisement data set to a roadside unit.
 35. Thenon-transitory computer-readable memory medium of claim 32, wherein thesoftware instructions are further executable to cause the mobile edgecomputing device to: provide the generated services advertisement dataset to the autonomous vehicle; and receive a services subscription dataset from the autonomous vehicle, wherein the provision of the serviceaccess is based on the services subscription data set.
 36. Thenon-transitory computer-readable memory medium of claim 32, wherein thesoftware instructions are further executable to cause the mobile edgecomputing device to provide network-based caching of content forservices from a plurality of content delivery network providers.